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Three Case Studies of the Application of Energy Systems Optimization Best Practices for Automatic DemandResponse Yifu Shi Kelly Guiberteau Carlos Yagua, P.E. James Watt, P.E. Energy Systems Laboratory, Texas A&M University College.... INTRODUCTION The overall goal of the demandresponse program is to reduce facilities peak energy demand to reduce the cost of electricity for both Austin Energy and their customer. Reducing the demand mitigates the need to construct additional...

LBNL-3047E DemandResponse and Open Automated DemandResponse Opportunities for Data Centers G described in this report was coordinated by the DemandResponse Research Center and funded by the California. DemandResponse and Open Automated DemandResponse Opportunities for Data Centers. California Energy

Deep DemandResponse: The Case Study of the CITRIS Building at the University of California quality. We have made progress towards achieving deep demandresponse of 30% reduction of peak loads modeling expertise), and UC Berkeley (related demandresponse research including distributed wireless

Mass Market DemandResponse Mass Market DemandResponse Speaker(s): Karen Herter Date: July 24, 2002 - 12:00pm Location: Bldg. 90 Demandresponse programs are often quickly and poorly crafted in reaction to an energy crisis and disappear once the crisis subsides, ensuring that the electricity system will be unprepared when the next crisis hits. In this paper, we propose to eliminate the event-driven nature of demandresponse programs by considering demandresponsiveness a component of the utility obligation to serve. As such, demandresponse can be required as a condition of service, and the offering of demandresponse rates becomes a requirement of utilities as an element of customer service. Using this foundation, we explore the costs and benefits of a smart thermostat-based demandresponse system capable of two types of programs: (1) a mandatory,

DemandResponse Assessment INTRODUCTION This appendix provides more detail on some of the topics raised in Chapter 4, "DemandResponse" of the body of the Plan. These topics include 1. The features, advantages and disadvantages of the main options for stimulating demandresponse (price mechanisms

Sample records for demand response case from the National Library of Energy Beta (NLEBeta)

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This paper provides new evidence on customer demandresponse to hourly pricing from the largest and...real-time pricing...(RTP) program in the United States. RTP creates value by inducing load reductions at times...

DemandResponseDemandResponseDemandResponseDemandResponseDemandresponse provides an opportunity for consumers to play a significant role in the operation of the electric grid by reducing or shifting their electricity usage during peak periods in response to time-based rates or other forms of financial incentives. Demandresponse programs are being used by electric system planners and operators as resource options for balancing supply and demand. Such programs can lower the cost of electricity in wholesale markets, and in turn, lead to lower retail rates. Methods of engaging customers in demandresponse efforts include offering time-based rates such as time-of-use pricing, critical peak pricing, variable peak pricing, real time pricing, and critical peak rebates. It also includes direct load control programs which provide the

Abstract The PJM wholesale electricity market has evolved to promote open competition between existing generation resources, new generation resources, demand-response, and alternative technologies to supply services to support reliable power grid operations. PJM has adapted market rules and procedures to accommodate smaller alternative resources while maintaining and enhancing stringent reliability standards for grid operation. Although the supply resource mix has tended to be less operationally flexible, the development of smart grid technologies, breakthroughs in storage technologies, microgrid applications, distributed supply resources, and smart metering infrastructure have the potential to make power transmission, distribution, and consumption more flexible than in the past. Competitive market signals in forward capacity markets and grid service markets have resulted in substantial investment in demand-response and alternative technologies to provide reliability services to the grid operator. This chapter discusses these trends and the market mechanisms by which both system and market operators can manage and leverage these changes to maintain the reliability of the bulk electric power system.

Demandresponse is crucial for the incorporation of renewable energy into the grid. In this paper, we focus on a particularly promising industry for demandresponse: data centers. We use simulations to show that, not only are data centers large loads, ... Keywords: data center, demandresponse, power network, prediction based pricing

Advances in communications and control technology the strengthening of the Internet and the growing appreciation of the urgency to reduce demand side energy use are motivating the development of improvements in both energy efficiency and demandresponse (DR) systems in buildings. This paper provides a framework linking continuous energy management and continuous communications for automated demandresponse (Auto?DR) in various times scales. We provide a set of concepts for monitoring and controls linked to standards and procedures such as Open Automation DemandResponse Communication Standards (OpenADR). Basic building energy science and control issues in this approach begin with key building components systems end?uses and whole building energy performance metrics. The paper presents a framework about when energy is used levels of services by energy using systems granularity of control and speed of telemetry. DR when defined as a discrete event requires a different set of building service levels than daily operations. We provide examples of lessons from DR case studies and links to energy efficiency.

The report provides a look at the past, present, and future state of the market for demand/load response based upon market price signals. It is intended to provide significant value to individuals and companies who are considering participating in demandresponse programs, energy providers and ISOs interested in offering demandresponse programs, and consultants and analysts looking for detailed information on demandresponse technology, applications, and participants. The report offers a look at the current DemandResponse environment in the energy industry by: defining what demandresponse programs are; detailing the evolution of program types over the last 30 years; discussing the key drivers of current initiatives; identifying barriers and keys to success for the programs; discussing the argument against subsidization of demandresponse; describing the different types of programs that exist including:direct load control, interruptible load, curtailable load, time-of-use, real time pricing, and demand bidding/buyback; providing examples of the different types of programs; examining the enablers of demandresponse programs; and, providing a look at major demandresponse programs.

Sample records for demand response case from the National Library of Energy Beta (NLEBeta)

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This paper describes the results from the second season of research to develop and evaluate the performance of new Automated DemandResponse (Auto-DR) hardware and software technology in large facilities. DemandResponse (DR) is a set of activities to reduce or shift electricity use to improve the electric grid reliability and manage electricity costs. Fully-Automated DemandResponse does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. We refer to this as Auto-DR. The evaluation of the control and communications must be properly configured and pass through a set of test stages: Readiness, Approval, Price Client/Price Server Communication, Internet Gateway/Internet Relay Communication, Control of Equipment, and DR Shed Effectiveness. New commissioning tests are needed for such systems to improve connecting demandresponsive building systems to the electric grid demandresponse systems.

This paper describes strategies that can be used in commercial buildings to temporarily reduce electric load in response to electric grid emergencies in which supplies are limited or in response to high prices that would be incurred if these strategies were not employed. The demandresponse strategies discussed herein are based on the results of three years of automated demandresponse field tests in which 28 commercial facilities with an occupied area totaling over 11 million ft{sup 2} were tested. Although the demandresponse events in the field tests were initiated remotely and performed automatically, the strategies used could also be initiated by on-site building operators and performed manually, if desired. While energy efficiency measures can be used during normal building operations, demandresponse measures are transient; they are employed to produce a temporary reduction in demand. Demandresponse strategies achieve reductions in electric demand by temporarily reducing the level of service in facilities. Heating ventilating and air conditioning (HVAC) and lighting are the systems most commonly adjusted for demandresponse in commercial buildings. The goal of demandresponse strategies is to meet the electric shed savings targets while minimizing any negative impacts on the occupants of the buildings or the processes that they perform. Occupant complaints were minimal in the field tests. In some cases, ''reductions'' in service level actually improved occupant comfort or productivity. In other cases, permanent improvements in efficiency were discovered through the planning and implementation of ''temporary'' demandresponse strategies. The DR strategies that are available to a given facility are based on factors such as the type of HVAC, lighting and energy management and control systems (EMCS) installed at the site.

DemandResponse Research in Spain DemandResponse Research in Spain Speaker(s): IÃ±igo Cobelo Date: August 22, 2007 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Mary Ann Piette The Spanish power system is becoming increasingly difficult to operate. The peak load grows every year, and the permission to build new transmission and distribution infrastructures is difficult to obtain. In this scenario DemandResponse can play an important role, and become a resource that could help network operators. The present deployment of demandresponse measures is small, but this situation however may change in the short term. The two main Spanish utilities and the transmission network operator are designing research projects in this field. All customer segments are targeted, and the research will lead to pilot installations and tests.

DemandResponse & Energy Efficiency International Conference for Enhanced Building Operations ESL-IC-09-11-05 Proceedings of the Ninth International Conference for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 2 ?Less than 5..., 2009 4 An Innovative Solution to Get the Ball Rolling ? DemandResponse (DR) ? Monitoring Based Commissioning (MBCx) EnerNOC has a solution involving two complementary offerings. ESL-IC-09-11-05 Proceedings of the Ninth International Conference...

Predictive DemandResponse Predictive DemandResponse Controller Research Project Integrated Predictive DemandResponse Controller Research Project The U.S. Department of Energy (DOE) is currently conducting research into integrated predictive demandresponse (IPDR) controllers. The project team will attempt to design an IPDR controller so that it can be used in new or existing buildings or in collections of buildings. In the case of collections of buildings, they may be colocated on a single campus or remotely located as long as they are served by a single utility or independent service operator. Project Description This project seeks to perform the necessary applied research, development, and testing to provide a communications interface using industry standard open protocols and emerging National Institute of Standards and Technology

The DemandResponse Spinning Reserve project is a pioneeringdemonstration of how existing utility load-management assets can providean important electricity system reliability resource known as spinningreserve. Using aggregated demand-side resources to provide spinningreserve will give grid operators at the California Independent SystemOperator (CAISO) and Southern California Edison (SCE) a powerful, newtool to improve system reliability, prevent rolling blackouts, and lowersystem operating costs.

Demandresponse is seen as one of the resources ... expected to incentivize small consumers to participate in demandresponse. This chapter models the involvement of small consumers in demandresponse programs wi...

Sample records for demand response case from the National Library of Energy Beta (NLEBeta)

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#12;#12;2008 Assessment of DemandResponse and Advanced Metering Staff Report Federal Energy metering penetration and potential peak load reduction from demandresponse have increased since 2006. Significant activity to promote demandresponse or to remove barriers to demandresponse occurred at the state

THE STATE OF DEMANDRESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demandresponse can help reduce the threat of planned rotational outages. Demandresponse is also widely regarded as having

THE STATE OF DEMANDRESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demandresponse (DR) can.S. and internationally and lay out ideas that could help move California forward. KEY WORDS demandresponse, peak

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Measurement and Verification for Measurement and Verification for DemandResponse Prepared for the National Forum on the National Action Plan on DemandResponse: Measurement and Verification Working Group AUTHORS: Miriam L. Goldberg & G. Kennedy Agnew-DNV KEMA Energy and Sustainability National Forum of the National Action Plan on DemandResponse Measurement and Verification for DemandResponse was developed to fulfill part of the Implementation Proposal for The National Action Plan on DemandResponse, a report to Congress jointly issued by the U.S. Department of Energy (DOE) and the Federal Energy Regulatory Commission (FERC) in June 2011. Part of that implementation proposal called for a "National Forum" on demandresponse to be conducted by DOE and FERC. Given that demandresponse has matured, DOE and FERC decided that a "virtual" project

Opportunities for Automated DemandResponse in Wastewater Treatment Opportunities for Automated DemandResponse in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study Title Opportunities for Automated DemandResponse in Wastewater Treatment Facilities in California - Southeast Water Pollution Control Plant Case Study Publication Type Report LBNL Report Number LBNL-6056E Year of Publication 2012 Authors Olsen, Daniel, Sasank Goli, David Faulkner, and Aimee T. McKane Date Published 12/2012 Publisher CEC/LBNL Keywords market sectors, technologies Abstract This report details a study into the demandresponse potential of a large wastewater treatment facility in San Francisco. Previous research had identified wastewater treatment facilities as good candidates for demandresponse and automated demandresponse, and this study was conducted to investigate facility attributes that are conducive to demandresponse or which hinder its implementation. One years' worth of operational data were collected from the facility's control system, submetered process equipment, utility electricity demand records, and governmental weather stations. These data were analyzed to determine factors which affected facility power demand and demandresponse capabilities.

Many of today's advanced building control systems are designed to improve granularity of control for energy efficiency. Examples include direct digital controls for building heating, ventilation, and cooling systems (HVAC), and dimmable ballasts for continuous dimming for daylighting applications. This paper discusses recent research on the use of new and existing controls in commercial buildings for integrated energy efficiency and demandresponse (DR). The paper discusses the use of DR controls strategies in commercial buildings and provides specific details on DR control strategy design concepts for a new building in New York. We present preliminary results from EnergyPlus simulations of the DR strategies at the New York Times Headquarters building currently under construction. The DR strategies at the Times building involve unique state of the art systems with dimmable ballasts, movable shades on the glass facade, and underfloor air HVAC. The simulation efforts at this building are novel, with an innovative building owner considering DR and future DR program participation strategies during the design phase. This paper also discusses commissioning plans for the DR strategies. The trends in integration of various systems through the EMCS, master versus supervisory controls and dynamic operational modes concepts are presented and future research directions are outlined.

Sample records for demand response case from the National Library of Energy Beta (NLEBeta)

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Response to changes in demand/supply through improved marketing 21.2 #12;#12;111 Impacts of changes log demand in 1995. The composites board mills operating in Korea took advantage of flexibility environment changes on the production mix, some economic indications, statistics of demand and supply of wood

Response to changes in demand/supply through improved marketing 21.2 http with the mill consuming 450 000 m3 , amounting to 30% of total plywood log demand in 1995. The composites board, statistics of demand and supply of wood, costs and competitiveness were analysed. The reactions

Distributed Intelligent Automated Demand Distributed Intelligent Automated DemandResponse (DIADR) Building Management System Distributed Intelligent Automated DemandResponse (DIADR) Building Management System The U.S. Department of Energy (DOE) is currently conducting research into distributed intelligent-automated demandresponse (DIADR) building management systems. Project Description This project aims to develop a DIADR building management system with intelligent optimization and control algorithms for demand management, taking into account a multitude of factors affecting cost including: Comfort Heating, ventilating, and air conditioning (HVAC) Lighting Other building systems Climate Usage and occupancy patterns. The key challenge is to provide the demandresponse the ability to address more and more complex building systems that include a variety of loads,

Envision a journey about 10 years into a future where demandresponse is actually integrated into the policies, standards, and operating practices of electric utilities. Here's a bottom-up view of how demandresponse actually works, as seen through the eyes of typical customers, system operators, utilities, and regulators. (author)

This paper reviews the relationship between energy efficiency and demandresponse and discusses approaches and barriers to coordinating energy efficiency and demandresponse. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demandresponse is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demandresponse resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demandresponse potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demandresponse and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demandresponse programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

David Kathan, Ph.D David Kathan, Ph.D Federal Energy Regulatory Commission U.S. DOE Electricity Advisory Committee October 29, 2010 DemandResponse as Power System Resources The author's views do not necessarily represent the views of the Federal Energy Regulatory Commission 2 DemandResponse * FERC (Order 719) defines demandresponse as: - A reduction in the consumption of electric energy by customers from their expected consumption in response to an increase in the price of electric energy or to in incentive payments designed to induce lower consumption of electric energy. * The National Action Plan on DemandResponse released by FERC staff broadens this definition to include - Consumer actions that can change any part of the load profile of a utility or region, not just the period of peak usage

Coordination of Energy Efficiency and DemandResponse Coordination of Energy Efficiency and DemandResponse Title Coordination of Energy Efficiency and DemandResponse Publication Type Report Refereed Designation Unknown Year of Publication 2010 Authors Goldman, Charles A., Michael Reid, Roger Levy, and Alison Silverstein Pagination 74 Date Published 01/2010 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract This paper reviews the relationship between energy efficiency and demandresponse and discusses approaches and barriers to coordinating energy efficiency and demandresponse. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025.1 Improving energy efficiency in our homes, businesses, schools, governments, and industries-which consume more than 70 percent of the nation's natural gas and electricity-is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demandresponse is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demandresponse resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demandresponse potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that "the combination of demandresponse and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW" by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demandresponse programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

Paying customers to refrain from purchasing products they want seems to run counter to the normal operation of markets. Demandresponse should be interpreted not as a supply-side resource but as a secondary market that attempts to correct the misallocation of electricity among electric users caused by regulated average rate tariffs. In a world with costless metering, the DR solution results in inefficiency as measured by deadweight losses. (author)

DemandResponse This is the first of the Council's power plans to treat demandresponse the resource and describes some of the potential advantages and problems of the development of demandresponse. WHAT IS DEMANDRESPONSE? Demandresponse is a change in customers' demand for electricity corresponding

National Council on Electricity Policy: Electric Transmission Series for State Offi National Council on Electricity Policy: Electric Transmission Series for State Offi cials DemandResponse and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials DemandResponse and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Prepared by the U.S. DemandResponse Coordinating Committee for The National Council on Electricity Policy Fall 2008 i National Council on Electricity Policy: Electric Transmission Series for State Offi cials DemandResponse and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials The National Council on Electricity Policy is funded by the U.S. Department of Energy and the U.S. Environmental Protection Agency. The views and opinions expressed herein are strictly those of the

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Industrial facilities universally struggle with escalating energy costs. EnerNOC will demonstrate how commercial, industrial, and institutional end-users can capitalize on their existing assets—at no cost and no risk. Demandresponse, the voluntary...

Critical peak pricing and peak time rebate programs offer benefits by increasing system reliability, and therefore, reducing capacity needs of the electric power system. These benefits, however, decrease substantially as the size of the programs grows relative to the system size. More flexible schemes for deployment of demandresponse can help address the decreasing returns to scale in capacity value, but more flexible demandresponse has decreasing returns to scale as well. (author)

Software demonstration: DemandResponse Quick Assessment Tool Software demonstration: DemandResponse Quick Assessment Tool Speaker(s): Peng Xu Date: February 4, 2008 - 12:00pm Location: 90-3122 The potential for utilizing building thermal mass for load shifting and peak demand reduction has been demonstrated in a number of simulation, laboratory, and field studies. The DemandResponse Quick Assessment Tools developed at LBNL will be demonstrated. The tool is built on EnergyPlus simulation and is able to evaluate and compare different DR strategies, such as global temperature reset, chiller cycling, supply air temperature reset, etc. A separate EnergyPlus plotting tool will also be demonstrated during this seminar. Users can use the tool to test EnergyPlus models, conduct parametric analysis, or compare multiple EnergyPlus simulation

LBNL-6560E Analysis of Open Automated DemandResponse Deployments in California and Guidelines The work described in this report was coordinated by the DemandResponse Research. #12; #12;Abstract This report reviews the Open Automated DemandResponse

, there are also huge opportunities for demandresponse in the industrial sector. This paper describes some of the demandresponse initiatives that are currently active in New York State, explaining applicability of industrial facilities. Next, we discuss demand...

Secure Demand Shaping for Smart Grid On constructing probabilistic demandresponse schemes. Developing novel schemes for demandresponse in smart electric gird is an increasingly active research area/SCADA for demandresponse in smart infrastructures face the following dilemma: On one hand, in order to increase

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Proper modeling of end use loads is very important in order to predict their behavior, and how they interact with the power system, including voltage and temperature dependencies, power system and load control functions, and the complex interactions that occur between devices in such an interconnected system. This paper develops multi-state time variant residential appliance models with demandresponse enabled capabilities in the GridLAB-DTM simulation environment. These models represent not only the baseline instantaneous power demand and energy consumption, but the control systems developed by GE Appliances to enable response to demandresponse signals and the change in behavior of the appliance in response to the signal. These DR enabled appliances are simulated to estimate their capability to reduce peak demand and energy consumption.

Barrier Immune Radio Communications for DemandResponse Barrier Immune Radio Communications for DemandResponse Title Barrier Immune Radio Communications for DemandResponse Publication Type Report LBNL Report Number LBNL-2294e Year of Publication 2009 Authors Rubinstein, Francis M., Girish Ghatikar, Jessica Granderson, Paul Haugen, Carlos Romero, and David S. Watson Keywords technologies Abstract Various wireless technologies were field-tested in a six-story laboratory building to identify wireless technologies that can scale for future DR applications through very low node density power consumption, and unit cost. Data analysis included analysis of the signal-to-noise ratio (SNR), packet loss, and link quality at varying power levels and node densities. The narrowband technologies performed well, penetrating the floors of the building with little loss and exhibiting better range than the wideband technology. 900 MHz provided full coverage at 1 watt and substantially complete coverage at 500 mW at the test site. 900 MHz was able to provide full coverage at 100 mW with only one additional relay transmitter, and was the highest-performing technology in the study. 2.4 GHz could not provide full coverage with only a single transmitter at the highest power level tested (63 mW). However, substantially complete coverage was provided at 2.4 GHz at 63 mW with the addition of one repeater node.

Design and Operation of an Open, Interoperable Automated DemandResponse Design and Operation of an Open, Interoperable Automated DemandResponse Infrastructure for Commercial Buildings Title Design and Operation of an Open, Interoperable Automated DemandResponse Infrastructure for Commercial Buildings Publication Type Journal Article LBNL Report Number LBNL-2340e Year of Publication 2009 Authors Piette, Mary Ann, Girish Ghatikar, Sila Kiliccote, David S. Watson, Edward Koch, and Dan Hennage Journal Journal of Computing Science and Information Engineering Volume 9 Issue 2 Keywords communication and standards, market sectors, openadr Abstract This paper describes the concept for and lessons from the development and field-testing of an open, interoperable communications infrastructure to support automated demandresponse (auto-DR). Automating DR allows greater levels of participation, improved reliability, and repeatability of the DR in participating facilities. This paper also presents the technical and architectural issues associated with auto-DR and description of the demandresponse automation server (DRAS), the client/server architecture-based middle-ware used to automate the interactions between the utilities or any DR serving entity and their customers for DR programs. Use case diagrams are presented to show the role of the DRAS between utility/ISO and the clients at the facilities.

94E 94E Barrier Immune Radio Communications for DemandResponse F. Rubinstein, G. Ghatikar, J. Granderson, D. Watson Lawrence Berkeley National Laboratory P. Haugen, C. Romero Lawrence Livermore National Laboratory February 2009 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe

Abstract Traditional electricity grid offers demand side management (DSM) programs for industrial plants and commercial buildings; there is no such program for residential consumers because of the lack of effective automation tools and efficient information and communication technologies (ICTs). Smart Grid is, by definition, equipped with modern automation tools such as home energy management system (HEMS), and ICTs. HEMS is an intelligent system that performs planning, monitoring and control functions of the energy utilization within premises. It is intended to offer desirable demandresponse according to system conditions and price value signaled by the utility. HEMS enables smart appliances to counter demandresponse programs according to the comfort level and priority set by the consumer. Demandresponse can play a key role to ensure sustainable and reliable electricity supply by reducing future generation cost, electricity prices, CO2 emission and electricity consumption at peak times. This paper focuses on the review of \\{HEMSs\\} and enabled demandresponse (DR) programs in various scenarios as well as incorporates various DR architectures and models employed in the smart grid. A comprehensive case study along with simulations and numerical analysis has also been presented.

The restructuring of regional electricity markets in the U.S. has been accompanied by numerous problems, including generation capacity shortages, transmission congestion, wholesale price volatility, and reduced system reliability. These problems have created significant new opportunities for technologies and business approaches that allow load serving entities and other aggregators, to control and manage the load patterns of their wholesale or retail end-users. These technologies and business approaches for manipulating end-user load shapes are known as Load Management or, more recently, DemandResponsive programs. Lawrence Berkeley National Laboratory (LBNL) is conducting case studies on innovative demandresponsive programs and presents preliminary results for five case studies in this paper. These case studies illustrate the diversity of market participants and range of technologies and business approaches and focus on key program elements such as target markets, market segmentation and participation results; pricing scheme; dispatch and coordination; measurement, verification, and settlement; and operational results where available.

Over the past several years, interest in large-scale control of peak energy demand and total consumption has increased. While motivated by a number of factors, this interest has primarily been spurred on the demand side by the increasing cost of energy and, on the supply side by the limited ability of utilities to build sufficient electricity generation capacity to meet unrestrained future demand. To address peak electricity use DemandResponse (DR) systems are being proposed to motivate reductions in electricity use through the use of price incentives. DR systems are also be design to shift or curtail energy demand at critical times when the generation, transmission, and distribution systems (i.e. the 'grid') are threatened with instabilities. To be effectively deployed on a large-scale, these proposed DR systems need to be automated. Automation will require robust and efficient data communications infrastructures across geographically dispersed markets. The present availability of widespread Internet connectivity and inexpensive, reliable computing hardware combined with the growing confidence in the capabilities of distributed, application-level communications protocols suggests that now is the time for designing and deploying practical systems. Centralized computer systems that are capable of providing continuous signals to automate customers reduction of power demand, are known as DemandResponse Automation Servers (DRAS). The deployment of prototype DRAS systems has already begun - with most initial deployments targeting large commercial and industrial (C & I) customers. An examination of the current overall energy consumption by economic sector shows that the C & I market is responsible for roughly half of all energy consumption in the US. On a per customer basis, large C & I customers clearly have the most to offer - and to gain - by participating in DR programs to reduce peak demand. And, by concentrating on a small number of relatively sophisticated energy consumers, it has been possible to improve the DR 'state of the art' with a manageable commitment of technical resources on both the utility and consumer side. Although numerous C & I DR applications of a DRAS infrastructure are still in either prototype or early production phases, these early attempts at automating DR have been notably successful for both utilities and C & I customers. Several factors have strongly contributed to this success and will be discussed below. These successes have motivated utilities and regulators to look closely at how DR programs can be expanded to encompass the remaining (roughly) half of the state's energy load - the light commercial and, in numerical terms, the more important residential customer market. This survey examines technical issues facing the implementation of automated DR in the residential environment. In particular, we will look at the potential role of home automation networks in implementing wide-scale DR systems that communicate directly to individual residences.

This paper focuses on an analysis of demandresponse in a smart grid context, presenting the ... A fuzzy subtractive clustering method is applied to demandresponse on several domestic consumption scenarios and r...

Optimization of DemandResponse Through Peak Shaving G. Zakeri , D. Craigie , A. Philpott , M. Todd for the demandresponse of such a consumer. We will establish a monotonicity result that indicates fuel supply

Quantifying the Variable Effects of Systems with DemandResponse Resources Anupama Kowli and George in the electricity industry. In particular, there is a new class of consumers, called demandresponse resources (DRRs

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In this paper, we consider the problem of optimal demandresponse and energy storage management for a power consuming entity. The entity's objective is to find an optimal control policy for deciding how much load to consume, how much power to purchase from/sell to the power grid, and how to use the finite capacity energy storage device and renewable energy, to minimize his average cost, being the disutility due to load- shedding and cost for purchasing power. Due to the coupling effect of the finite size energy storage, such problems are challenging and are typically tackled using dynamic programming, which is often complex in computation and requires substantial statistical information of the system dynamics. We instead develop a low-complexity algorithm called DemandResponse with Energy Storage Management (DR-ESM). DR-ESM does not require any statistical knowledge of the system dynamics, including the renewable energy and the power prices. It only requires the entity to solve a small convex optimization pr...

DemandResponse Quick Assessment Tool DemandResponse Quick Assessment Tool Demandresponse quick assessment tool image The opportunities for demand reduction and cost savings with building demandresponsive controls vary tremendously with building type and location. This assessment tool will predict the energy and demand savings, the economic savings, and the thermal comfort impact for various demandresponsive strategies. Users of the tool will be asked to enter the basic building information such as types, square footage, building envelope, orientation, utility schedule, etc. The assessment tool will then use the prototypical simulation models to calculate the energy and demand reduction potential under certain demandresponsive strategies, such as precooling, zonal temperature set up, and chilled water loop and air loop set points

An Integrated Architecture for DemandResponse Communications and Control Michael LeMay, Rajesh for the MGA and ZigBee wireless communications. Index Terms DemandResponse, Advanced Meter Infrastructure. In principle this can be done with demandresponse techniques in which electricity users take measures

A First Look at Colocation DemandResponse Shaolei Ren Florida International University Mohammad A. Islam Florida International University ABSTRACT Large data centers can participate in demandresponse, the existing research has only considered demandresponse by owner-operated data centers (e.g., Google

LBNL-5319E Assessing the Control Systems Capacity for DemandResponse in California Industries in this report was coordinated by the DemandResponse Research Center and funded by the California Energy of the DemandResponse Research Center Industrial Controls Experts Working Group: Â· Jim Filanc, Southern

Optimal DemandResponse Based on Utility Maximization in Power Networks Na Li, Lijun Chen different appliances including PHEVs and batteries and propose a demandresponse approach based on utility. The utility company can thus use dynamic pricing to coordinate demandresponses to the benefit of the overall

Date: June 12, 2007 To: Pacific Northwest DemandResponse Project From: Rich Sedano/RAP and Chuck, 2007 meeting of the Pacific Northwest DemandResponse Project, we agreed to form three Working Groups for the evaluation of cost-effectiveness of DemandResponse resources. One potential outcome would be for state

Graphical language for identification of control strategies allowing DemandResponse David DA SILVA. This will allow the identification of the electric appliance availability for demandresponse control strategies to be implemented in terms of demandresponse for electrical appliances. Introduction An important part

Occupancy Based DemandResponse HVAC Control Strategy Varick L. Erickson University of California an efficient demandresponse HVAC control strategy, actual room usage must be considered. Temperature and CO2 are used for simulations but not for predictive demandresponse strategies. In this paper, we develop

LBNL-5958E DemandResponse Providing Ancillary Services A Comparison of Opportunities Government or any agency thereof or The Regents of the University of California. #12;DemandResponse System Reliability, DemandResponse (DR), Electricity Markets, Smart Grid Abstract Interest in using

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LBNL-6108E Opportunities for DemandResponse in California Agricultural Irrigation: A Scoping Study was sponsored in part by the DemandResponse Research Center which is funded by the California .................................. 2 Best Opportunities for DemandResponse and Permanent Load Shifting Programs.............. 3

LBNL-5555E Fast Automated DemandResponse to Enable the Integration of Renewable Resources David S The work described in this report was coordinated by the DemandResponse Research Center and funded ABSTRACT This study examines how fast automated demandresponse (AutoDR) can help mitigate grid balancing

Two Market Models for DemandResponse in Power Networks Lijun Chen, Na Li, Steven H. Low and John C-- In this paper, we consider two abstract market models for designing demandresponse to match power supply as oligopolistic markets, and propose distributed demandresponse algorithms to achieve the equilibria. The models

LBNL-1335E Opportunities, Barriers and Actions for Industrial DemandResponse in California A.T. Mc of Global Energy Partners. This work described in this report was coordinated by the DemandResponseDemandResponse in California. PIER Industrial/Agricultural/Water EndUse Energy Efficiency Program. CEC

LBNL-1470E LBNL-1470E Retail DemandResponse in Southwest Power Pool Ranjit Bharvirkar, Grayson Heffner and Charles Goldman Lawrence Berkeley National Laboratory Environmental Energy Technologies Division January 2009 The work described in this report was funded by the Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under Contract No. DE-AC02-05CH11231. ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Disclaimer This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of

044E 044E ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Coordination of Energy Efficiency and DemandResponse Charles Goldman, Michael Reid, Roger Levy and Alison Silverstein Environmental Energy Technologies Division January 2010 The work described in this report was funded by the Department of Energy Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under Contract No. DE-AC02- 05CH11231. Disclaimer This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes

DemandResponse - Policy: More Information DemandResponse - Policy: More Information DemandResponse - Policy: More Information OE's commitment to ensuring non-wires options to modernize the nation's electricity delivery system includes ongoing support of a number of national and regional activities in support of demandresponse. The New England DemandResponse Initiative (NEDRI), OE's initial endeavor to assist states with non-wire solutions, was created to develop a comprehensive, coordinated set of demandresponse programs for the New England regional power markets. NEDRI's goal was to outline workable market rules, public policies, and regulatory criteria to incorporate customer-based demandresponse resources into New England's electricity markets and power systems. NEDRI promoted best practices and coordinated

FERC Presendation: DemandResponse as Power System Resources, FERC Presendation: DemandResponse as Power System Resources, October 29, 2010 FERC Presendation: DemandResponse as Power System Resources, October 29, 2010 Federal Energy Regulatory Commission (FERC) presentation on demandresponse as power system resources before the Electicity Advisory Committee, October 29, 2010 DemandResponse as Power System Resources More Documents & Publications A National Forum on DemandResponse: Results on What Remains to Be Done to Achieve Its Potential - Cost-Effectiveness Working Group Loads Providing Ancillary Services: Review of International Experience Benefits of DemandResponse in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 (February 2006)

, with an estimated price elasticity of -0.2, is not yet very responsive to price variation. A regional water model water pricing. Keywords: demand elasticity, France, water pricing, residential water demand, simulationSimulating the impact of pricing policies on residential water demand: a Southern France case study

Article Estimating the Price Elasticity of Residential Water Demand: The Case of Phoenix, Arizona to such changes requires understanding the responsiveness of water demand to price changes. We estimate the price://aepp.oxfordjournals.org/Downloadedfrom #12;measures. In this paper we apply a method for estimating the price elasticity of water demand

Wastewater treatment is an energy intensive process which, together with water treatment, comprises about three percent of U.S. annual energy use. Yet, since wastewater treatment facilities are often peripheral to major electricity-using industries, they are frequently an overlooked area for automated demandresponse opportunities. Demandresponse is a set of actions taken to reduce electric loads when contingencies, such as emergencies or congestion, occur that threaten supply-demand balance, and/or market conditions occur that raise electric supply costs. Demandresponse programs are designed to improve the reliability of the electric grid and to lower the use of electricity during peak times to reduce the total system costs. Open automated demandresponse is a set of continuous, open communication signals and systems provided over the Internet to allow facilities to automate their demandresponse activities without the need for manual actions. Automated demandresponse strategies can be implemented as an enhanced use of upgraded equipment and facility control strategies installed as energy efficiency measures. Conversely, installation of controls to support automated demandresponse may result in improved energy efficiency through real-time access to operational data. This paper argues that the implementation of energy efficiency opportunities in wastewater treatment facilities creates a base for achieving successful demand reductions. This paper characterizes energy use and the state of demandresponse readiness in wastewater treatment facilities and outlines automated demandresponse opportunities.

Rates and technologies for mass-market demandresponse Rates and technologies for mass-market demandresponse Title Rates and technologies for mass-market demandresponse Publication Type Conference Paper LBNL Report Number LBNL-50626 Year of Publication 2002 Authors Herter, Karen, Roger Levy, John Wilson, and Arthur H. Rosenfeld Conference Name 2002 ACEEE Summer Study on Energy Efficiency in Buildings Conference Location Pacific Grove, CA Keywords demandresponse, demandresponse and distributed energy resources center, demandresponse research center, rate programs & tariffs Abstract Demandresponse programs are often quickly and poorly crafted in reaction to an energy crisis and disappear once the crisis subsides, ensuring that the electricity system will be unprepared when the next crisis hits. In this paper, we propose to eliminate the event-driven nature of demandresponse programs by considering demandresponsiveness a component of the utility obligation to serve. As such, demandresponse can be required as a condition of service, and the offering of demandresponse rates becomes a requirement of utilities as an element of customer service. Using this foundation, we explore the costs and benefits of a smart thermostat-based demandresponse system capable of two types of programs: (1) a mandatory, system-operator controlled, contingency program, and (2) a voluntary, customer controlled, bill management program with rate-based incentives. Any demandresponse program based on this system could consist of either or both of these components. Ideally, these programs would be bundled, providing automatic load management through customer-programmed price response, plus up to 10 GW of emergency load shedding capability in California. Finally, we discuss options for and barriers to implementation of such a program in California.

Automated Price and DemandResponse Demonstration for Large Customers Automated Price and DemandResponse Demonstration for Large Customers in New York City using OpenADR booktitle International Conference for Enhanced Building Operations ICEBO year month address Montreal Quebec abstract p class p1 Open Automated DemandResponse OpenADR an XML based information exchange model is used to facilitate continuous price responsive operation and demandresponse participation for large commercial buildings in New York who are subject to the default day ahead hourly pricing We summarize the existing demandresponse programs in New York and discuss OpenADR communication prioritization of demandresponse signals and control methods Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management

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Mass Market DemandResponse and Variable Generation Integration Issues: A Mass Market DemandResponse and Variable Generation Integration Issues: A Scoping Study Title Mass Market DemandResponse and Variable Generation Integration Issues: A Scoping Study Publication Type Report Refereed Designation Unknown Year of Publication 2011 Authors Cappers, Peter, Andrew D. Mills, Charles A. Goldman, Ryan H. Wiser, and Joseph H. Eto Pagination 76 Date Published 10/2011 Publisher LBNL City Berkeley Keywords demandresponse, electricity markets and policy group, energy analysis and environmental impacts department, renewable generation integration, smart grid Abstract The penetration of renewable generation technology (e.g., wind, solar) is expected to dramatically increase in the United States during the coming years as many states are implementing policies to expand this sector through regulation and/or legislation. It is widely understood, though, that large scale deployment of certain renewable energy sources, namely wind and solar, poses system integration challenges because of its variable and often times unpredictable production characteristics (NERC, 2009). Strategies that rely on existing thermal generation resources and improved wind and solar energy production forecasts to manage this variability are currently employed by bulk power system operators, although a host of additional options are envisioned for the near future. Demandresponse (DR), when properly designed, could be a viable resource for managing many of the system balancing issues associated with integrating large-scale variable generation (VG) resources (NERC, 2009). However, demand-side options would need to compete against strategies already in use or contemplated for the future to integrate larger volumes of wind and solar generation resources. Proponents of smart grid (of which Advanced Metering Infrastructure or AMI is an integral component) assert that the technologies associated with this new investment can facilitate synergies and linkages between demand-side management and bulk power system needs. For example, smart grid proponents assert that system-wide implementation of advanced metering to mass market customers (i.e., residential and small commercial customers) as part of a smart grid deployment enables a significant increase in demandresponse capability.1 Specifically, the implementation of AMI allows electricity consumption information to be captured, stored and utilized at a highly granular level (e.g., 15-60 minute intervals in most cases) and provides an opportunity for utilities and public policymakers to more fully engage electricity customers in better managing their own usage through time-based rates and near-real time feedback to customers on their usage patterns while also potentially improving the management of the bulk power system. At present, development of time-based rates and demandresponse programs and the installation of variable generation resources are moving forward largely independent of each other in state and regional regulatory and policy forums and without much regard to the complementary nature of their operational characteristics.2 By 2020, the electric power sector is expected to add ~65 million advanced meters3 (which would reach ~47% of U.S. households) as part of smart grid and AMI4 deployments (IEE, 2010) and add ~40-80 GW of wind and solar capacity (EIA, 2010). Thus, in this scoping study, we focus on a key question posed by policymakers: what role can the smart grid (and its associated enabling technology) play over the next 5-10 years in helping to integrate greater penetration of variable generation resources by providing mass market customers with greater access to demandresponse opportunities? There is a well-established body of research that examines variable generation integration issues as well as demandresponse potential, but the nexus between the two has been somewhat neglected by the industry. The studies that have been conducted are informative concerning what could be accomplished with strong broad-based support for the expansion of demandresponse opportunities, but typically do not discuss the many barriers that stand in the way of reaching this potential. This study examines how demand side resources could be used to integrate wind and solar resources in the bulk power system, identifies barriers that currently limit the use of demand side strategies, and suggests several factors that should be considered in assessing alternative strategies that can be employed to integrate wind and solar resources in the bulk power system. It is difficult to properly gauge the role that DR could play in managing VG integration issues in the near future without acknowledging and understanding the entities and institutions that govern the interactions between variable generation and mass market customers (see Figure ES-1). Retail entities, like load-serving entities (LSE) and aggregators of retail customers (ARC), harness the demandresponse opportunities of mass market customers through tariffs (and DR programs) that are approved by state regulatory agencies or local governing entities (in the case of public power). The changes in electricity consumption induced by DR as well as the changes in electricity production due to the variable nature of wind and solar generation technologies is jointly managed by bulk power system operators. Bulk power system operators function under tariffs approved by the Federal Energy Regulatory Commission (FERC) and must operate their systems in accordance with rules set by regional reliability councils. These reliability rules are derived from enforceable standards that are set by the North American Electric Reliability Corporation (NERC) and approved by federal regulators. Thus, the role that DR can play in managing VG integration issues is contingent on what opportunities state and local regulators are willing to approve and how customers' response to the DR opportunities can be integrated into the bulk power system both electrically (due to reliability rules) and financially (due to market rules).

Dynamic retail electricity pricing, especially real-time pricing (RTP), has been widely heralded as a panacea for providing much-needed demandresponse in electricity markets. However, in designing default service for competitive retail markets, demandresponse often appears to be an afterthought. But that may be changing as states that initiated customer choice in the past 5-7 years reach an important juncture in retail market design. Most states with retail choice established an initial transitional period, during which utilities were required to offer a default or ''standard offer'' generation service, often at a capped or otherwise administratively-determined rate. Many retail choice states have reached, or are nearing, the end of their transitional period and several states have adopted an RTP-type default service for large commercial and industrial (C&I) customers. Are these initiatives motivated by the desire to induce greater demandresponse, or is RTP being called upon to serve a different role in competitive markets? Surprisingly, we found that in most cases, the primary reason for adopting RTP as the default service was not to encourage demandresponse, but rather to advance policy objectives related to the development of competitive retail markets. However, we also find that, if efforts are made in its design and implementation, default RTP service can also provide a solid foundation for developing price responsivedemand, creating an important link between wholesale and retail market transactions. This paper, which draws from a lengthier report, describes the experience to date with default RTP in the U.S., identifying findings related to its actual and potential role as an instrument for cultivating price responsivedemand [1]. For each of the five states currently with default RTP, we conducted a detailed review of the regulatory proceedings leading to its adoption. To further understand the intentions and expectations of those involved in its design and implementation, we also interviewed regulatory staff and utilities in each state, as well as eight of the most prominent competitive retail suppliers operating in these markets which, together, comprised about 60-65% of competitive C&I sales in the U.S. in 2004 [2].

Abstract This paper focuses on demandresponse in a smart grid scope using a fuzzy subtractive clustering technique for modeling demandresponse. Domestic consumption is classified into profiles in order to favorable cover the adequate modeling. The fuzzy subtractive clustering technique is applied to a case study of domestic consumption demandresponse with three scenarios and a comparison of the results is presented. The demandresponse developed model intends to support consumer's decisions given a compromise between the consumption imperative needs and possible economical benefits due to reshape and reschedule.

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Price ResponsiveDemand in New York Wholesale Electricity Market using Price ResponsiveDemand in New York Wholesale Electricity Market using OpenADR Title Price ResponsiveDemand in New York Wholesale Electricity Market using OpenADR Publication Type Report LBNL Report Number LBNL-5557E Year of Publication 2012 Authors Kim, Joyce Jihyun, and Sila Kiliccote Date Published 06/2012 Publisher LBNL/NYSERDA Keywords commercial, demandresponse, dynamic pricing, mandatory hourly pricing, open automated demandresponse, openadr, pilot studies & implementation, price responsivedemand Abstract In New York State, the default electricity pricing for large customers is Mandatory Hourly Pricing (MHP), which is charged based on zonal day-ahead market price for energy. With MHP, retail customers can adjust their building load to an economically optimal level according to hourly electricity prices. Yet, many customers seek alternative pricing options such as fixed rates through retail access for their electricity supply. Open Automated DemandResponse (OpenADR) is an XML (eXtensible Markup Language) based information exchange model that communicates price and reliability information. It allows customers to evaluate hourly prices and provide demandresponse in an automated fashion to minimize electricity costs. This document shows how OpenADR can support MHP and facilitate price responsivedemand for large commercial customers in New York City.

The report provides a study of the technologies that are crucial to the success of demandresponse programs. It takes a look at the historical development of demandresponse programs and analyzes how new technology is needed to enable demandresponse to make the transition from a small scale pilot operation to a mass market means of improving grid reliability. Additionally, the report discusses the key technologies needed to enable a large scale demandresponse effort and evaluates current efforts to develop and integrate these technologies. Finally, the report provides profiles of leading developers of these key technologies.

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The Pacific Gas and Electric Company (PG&E) is conducting a pilot program to investigate the technical feasibility of bidding certain demandresponse (DR) resources into the California Independent System Operator's (CAISO) day-ahead market for ancillary services nonspinning reserve. Three facilities, a retail store, a local government office building, and a bakery, are recruited into the pilot program. For each facility, hourly demand, and load curtailment potential are forecasted two days ahead and submitted to the CAISO the day before the operation as an available resource. These DR resources are optimized against all other generation resources in the CAISO ancillary service. Each facility is equipped with four-second real time telemetry equipment to ensure resource accountability and visibility to CAISO operators. When CAISO requests DR resources, PG&E's OpenADR (Open Automated DR) communications infrastructure is utilized to deliver DR signals to the facilities energy management and control systems (EMCS). The pre-programmed DR strategies are triggered without a human in the loop. This paper describes the automated system architecture and the flow of information to trigger and monitor the performance of the DR events. We outline the DR strategies at each of the participating facilities. At one site a real time electric measurement feedback loop is implemented to assure the delivery of CAISO dispatched demand reductions. Finally, we present results from each of the facilities and discuss findings.

The Interoperability of DemandResponse Resources Demonstration in NY (Interoperability Project) was awarded to Con Edison in 2009. The objective of the project was to develop and demonstrate methodologies to enhance the ability of customer sited DemandResponse resources to integrate more effectively with electric delivery companies and regional transmission organizations.

Response Opportunities in Industrial Refrigerated Warehouses in Response Opportunities in Industrial Refrigerated Warehouses in California Title DemandResponse Opportunities in Industrial Refrigerated Warehouses in California Publication Type Conference Paper LBNL Report Number LBNL-4837E Year of Publication 2011 Authors Goli, Sasank, Aimee T. McKane, and Daniel Olsen Conference Name 2011 ACEEE Summer Study on Energy Efficiency in Industry Date Published 08/2011 Conference Location Niagara Falls, NY Keywords market sectors, openadr, refrigerated warehouses Abstract Industrial refrigerated warehouses that implemented energy efficiency measures and have centralized control systems can be excellent candidates for Automated DemandResponse (Auto-DR) due to equipment synergies, and receptivity of facility managers to strategies that control energy costs without disrupting facility operations. Auto-DR utilizes OpenADR protocol for continuous and open communication signals over internet, allowing facilities to automate their DemandResponse (DR). Refrigerated warehouses were selected for research because: They have significant power demand especially during utility peak periods; most processes are not sensitive to short-term (2-4 hours) lower power and DR activities are often not disruptive to facility operations; the number of processes is limited and well understood; and past experience with some DR strategies successful in commercial buildings may apply to refrigerated warehouses. This paper presents an overview of the potential for load sheds and shifts from baseline electricity use in response to DR events, along with physical configurations and operating characteristics of refrigerated warehouses. Analysis of data from two case studies and nine facilities in Pacific Gas and Electric territory, confirmed the DR abilities inherent to refrigerated warehouses but showed significant variation across facilities. Further, while load from California's refrigerated warehouses in 2008 was 360 MW with estimated DR potential of 45-90 MW, actual achieved was much less due to low participation. Efforts to overcome barriers to increased participation may include, improved marketing and recruitment of potential DR sites, better alignment and emphasis on financial benefits of participation, and use of Auto-DR to increase consistency of participation.

the Control Systems Capacity for DemandResponse in California the Control Systems Capacity for DemandResponse in California Industries Title Assessing the Control Systems Capacity for DemandResponse in California Industries Publication Type Report LBNL Report Number LBNL-5319E Year of Publication 2012 Authors Ghatikar, Girish, Aimee T. McKane, Sasank Goli, Peter L. Therkelsen, and Daniel Olsen Date Published 01/2012 Publisher CEC/LBNL Keywords automated dr, controls and automation, demandresponse, dynamic pricing, industrial controls, market sectors, openadr Abstract California's electricity markets are moving toward dynamic pricing models, such as real-time pricing, within the next few years, which could have a significant impact on an industrial facility's cost of energy use during the times of peak use. Adequate controls and automated systems that provide industrial facility managers real-time energy use and cost information are necessary for successful implementation of a comprehensive electricity strategy; however, little is known about the current control capacity of California industries. To address this gap, Lawrence Berkeley National Laboratory, in close collaboration with California industrial trade associations, conducted a survey to determine the current state of controls technologies in California industries. This study identifies sectors that have the technical capability to implement DemandResponse (DR) and Automated DemandResponse (Auto-DR). In an effort to assist policy makers and industry in meeting the challenges of real-time pricing, facility operational and organizational factors were taken into consideration to generate recommendations on which sectors DemandResponse efforts should be focused. Analysis of the survey responses showed that while the vast majority of industrial facilities have semi- or fully automated control systems, participation in DemandResponse programs is still low due to perceived barriers. The results also showed that the facilities that use continuous processes are good DemandResponse candidates. When comparing facilities participating in DemandResponse to those not participating, several similarities and differences emerged. DemandResponse-participating facilities and non-participating facilities had similar timings of peak energy use, production processes, and participation in energy audits. Though the survey sample was smaller than anticipated, the results seemed to support our preliminary assumptions. Demonstrations of Auto-DemandResponse in industrial facilities with good control capabilities are needed to dispel perceived barriers to participation and to investigate industrial subsectors suggested of having inherent DemandResponse potential.

FERC's Supplemental Notice of Public Rulemaking addresses the question of proper compensation for demandresponse in organized wholesale electricity markets. Assuming that the Commission would proceed with the proposal ''to require tariff provisions allowing demandresponse resources to participate in wholesale energy markets by reducing consumption of electricity from expected levels in response to price signals, to pay those demandresponse resources, in all hours, the market price of energy for such reductions,'' the Commission posed questions about applying a net benefits test and rules for cost allocation. This article summarizes critical points and poses implications for the issues of net benefit tests and cost allocation. (author)

Industrial refrigerated warehouses that implemented energy efficiency measures and have centralized control systems can be excellent candidates for Automated DemandResponse (Auto-DR) due to equipment synergies, and receptivity of facility managers to strategies that control energy costs without disrupting facility operations. Auto-DR utilizes OpenADR protocol for continuous and open communication signals over internet, allowing facilities to automate their DemandResponse (DR). Refrigerated warehouses were selected for research because: They have significant power demand especially during utility peak periods; most processes are not sensitive to short-term (2-4 hours) lower power and DR activities are often not disruptive to facility operations; the number of processes is limited and well understood; and past experience with some DR strategies successful in commercial buildings may apply to refrigerated warehouses. This paper presents an overview of the potential for load sheds and shifts from baseline electricity use in response to DR events, along with physical configurations and operating characteristics of refrigerated warehouses. Analysis of data from two case studies and nine facilities in Pacific Gas and Electric territory, confirmed the DR abilities inherent to refrigerated warehouses but showed significant variation across facilities. Further, while load from California's refrigerated warehouses in 2008 was 360 MW with estimated DR potential of 45-90 MW, actual achieved was much less due to low participation. Efforts to overcome barriers to increased participation may include, improved marketing and recruitment of potential DR sites, better alignment and emphasis on financial benefits of participation, and use of Auto-DR to increase consistency of participation.

Response to several FOIA requests - Renewable Energy. Demand for Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. nepdg_251_500.pdf. Demand for Fossil Fuels. Renewable sources of power. Demand for fossil fuels surely will overrun supply sooner or later, as indeed it already has in the casc of United States domestic oil drilling. Recognition also is growing that our air and land can no longer absorb unlimited quantities of waste from fossil fuel extraction and combustion. As that day draws nearer, policymakers will have no realistic alternative but to turn to sources of power that today make up a viable but small part of America's energy picture. And they will be

Demand Shifting With Thermal Mass in Large Commercial Buildings: CaseDemand Shifting With Thermal Mass in Large Commercial Buildings: Case Studies and Tools Speaker(s): Peng Xu Date: March 9, 2007 - 12:00pm Location: 90-3122 The idea of pre-cooling and demand limiting is to pre-cool buildings at night or in the morning during off-peak hours, storing cooling energy in the building thermal mass and thereby reducing cooling loads during the peak periods. Savings are achieved by reducing on-peak energy and demand charges. The potential for utilizing building thermal mass for load shifting and peak demand reduction has been demonstrated in a number of simulation, laboratory, and field studies. Case studies in a number of office buildings in California has found that a simple demand limiting strategy reduced the chiller power by 20-100% (0.5-2.3W/ft2) during six

DemandResponse in Southwest Power Pool DemandResponse in Southwest Power Pool Retail DemandResponse in Southwest Power Pool In 2007, the Southwest Power Pool (SPP) formed the Customer Response Task Force (CRTF) to identify barriers to deploying demandresponse (DR) resources in wholesale markets and develop policies to overcome these barriers. One of the initiatives of this Task Force was to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating practices. This report describes the results of a comprehensive survey conducted by LBNL in support of the Customer Response Task Force and discusses policy implications for integrating legacy retail DR programs and dynamic pricing tariffs into wholesale markets in the SPP region.

Abstract Demandresponse (DR) has been considered as a generation alternative to improve the reliability indices of the system and load point. However, when the demand resources scheduled in the DR market fail to result in demand reductions, it can potentially bring new problems associated with maintaining a reliable supply. In this paper, a reliability model of the demand resource is constructed considering customers’ behaviors in the same form as conventional generation units, where the availability and unavailability are associated with the simple two-state model. The reliability model is generalized by a multi-state model. In the integrated power market with DR, market players provide the demand reduction and generation, which are represented by an equivalent multi-state demandresponse and generation, respectively. The reliability indices of the system and load point are evaluated using the optimal power flow by minimizing the summation of load curtailments with various constraints.

DemandResponse in Electricity Markets and DemandResponse in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 (February 2006) Benefits of DemandResponse in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 (February 2006) Most electricity customers see electricity rates that are based on average electricity costs and bear little relation to the true production costs of electricity as they vary over time. Demandresponse is a tariff or program established to motivate changes in electric use by end-use customers in response to changes in the price of electricity over time, or to give

in U.S. Electricity Markets: Empirical Evidence in U.S. Electricity Markets: Empirical Evidence DemandResponse in U.S. Electricity Markets: Empirical Evidence The work described in this paper was funded by the Office of Electricity Delivery and Energy Reliability, Permitting, Siting and Analysis of the U.S. Department of Energy under contract No. DE-AC02-05CH11231. The authors are solely responsible for any omissions or errors contained herein. DemandResponse in U.S. Electricity Markets: Empirical Evidence More Documents & Publications DemandResponse National Trends: Implications for the West? Benefits of DemandResponse in Electricity Markets and Recommendations for Achieving Them. A report to the United States Congress Pursuant to Section 1252 of the Energy Policy Act of 2005 (February 2006)

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1 1 COMMENTS OF THE DEMANDRESPONSE AND SMART GRID COALITION Department of Energy Implementing the National Broadband Plan by Empowering Consumers and the Smart Grid: Data Access, Third Party Use, and Privacy July 12, 2010 The DemandResponse and Smart Grid Coalition (DRSG) 1 , the trade association for companies that provide products and services in the areas of demandresponse and smart grid technologies, respectfully submits its comments to the Department of Energy's Request for Information "Implementing the National Broadband Plan by Empowering Consumers and the Smart Grid: Data Access, Third Party Use, and Privacy."

Modeling, Analysis, and Control of DemandResponse Resources Modeling, Analysis, and Control of DemandResponse Resources Speaker(s): Johanna Mathieu Date: April 27, 2012 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Sila Kiliccote While the traditional goal of an electric power system has been to control supply to fulfill demand, the demand-side can play an active role in power systems via DemandResponse (DR). Recent DR programs have focused on peak load reduction in commercial buildings and industrial facilities (C&I facilities). We present a regression-based baseline model, which allows us to quantify DR performance. We use this baseline model to understand the performance of C&I facilities participating in an automated dynamic pricing DR program in California. In this program, facilities are

Demandresponse and dynamic pricing programs are expected to play increasing roles in the modern Smart Grid environment. While direct load control of end-use loads has existed for decades, price driven response programs are only beginning to be explored at the distribution level. These programs utilize a price signal as a means to control demand. Active markets allow customers to respond to fluctuations in wholesale electrical costs, but may not allow the utility to control demand. Transactive markets, utilizing distributed controllers and a centralized auction can be used to create an interactive system which can limit demand at key times on a distribution system, decreasing congestion. With the current proliferation of computing and communication resources, the ability now exists to create transactive demandresponse programs at the residential level. With the combination of automated bidding and response strategies coupled with education programs and customer response, emerging demandresponse programs have the ability to reduce utility demand and congestion in a more controlled manner. This paper will explore the effects of a residential double-auction market, utilizing transactive controllers, on the operation of an electric power distribution system.

Grid Integration of Aggregated DemandResponse, Part 1: Load Availability Grid Integration of Aggregated DemandResponse, Part 1: Load Availability Profiles and Constraints for the Western Interconnection Title Grid Integration of Aggregated DemandResponse, Part 1: Load Availability Profiles and Constraints for the Western Interconnection Publication Type Report LBNL Report Number LBNL-6417E Year of Publication 2013 Authors Olsen, Daniel, Nance Matson, Michael D. Sohn, Cody Rose, Junqiao Han Dudley, Sasank Goli, Sila Kiliccote, Marissa Hummon, David Palchak, Paul Denholm, Jennie Jorgenson, and Ookie Ma Date Published 09/2013 Abstract Demandresponse (DR) has the potential to improve electric grid reliability and reduce system operation costs. However, including DR in grid modeling can be difficult due to its variable and non-traditional response characteristics, compared to traditional generation. Therefore, efforts to value the participation of DR in procurement of grid services have been limited. In this report, we present methods and tools for predicting demandresponse availability profiles, representing their capability to participate in capacity, energy, and ancillary services. With the addition of response characteristics mimicking those of generation, the resulting profiles will help in the valuation of the participation of demandresponse through production cost modeling, which informs infrastructure and investment planning.

Technologies and Demonstration in New York City Technologies and Demonstration in New York City using OpenADR Title Automated DemandResponse Technologies and Demonstration in New York City using OpenADR Publication Type Report LBNL Report Number LBNL-6470E Year of Publication 2013 Authors Kim, Joyce Jihyun, Sila Kiliccote, and Rongxin Yin Date Published 09/2013 Publisher LBNL/NYSERDA Abstract Demandresponse (DR) - allowing customers to respond to reliability requests and market prices by changing electricity use from their normal consumption pattern - continues to be seen as an attractive means of demand-side management and a fundamental smart-grid improvement that links supply and demand. Since October 2011, the DemandResponse Research Center at Lawrence Berkeley National Laboratory and New York State Energy Research and Development Authority have conducted a demonstration project enabling Automated DemandResponse (Auto-DR) in large commercial buildings located in New York City using Open Automated DemandResponse (OpenADR) communication protocols. In particular, this project focuses on demonstrating how OpenADR can automate and simplify interactions between buildings and various stakeholders in New York State including the independent system operator, utilities, retail energy providers, and curtailment service providers. In this paper, we present methods to automate control strategies via building management systems to provide event-driven demandresponse, price response and demand management based on OpenADR signals. We also present cost control opportunities under day-ahead hourly pricing for large customers and Auto-DR control strategies developed for demonstration buildings. Lastly, we discuss the communication architecture and Auto-DR system designed for the demonstration project to automate price response and DR participation.

Emerging standards such as OpenADR enable DemandResponse (DR) Resources to interact directly with Utilities and Independent System Operators to allow their facility automation equipment to respond to a variety of DR signals ranging from day ahead to real time ancillary services. In addition, there are Aggregators in today’s markets who are capable of bringing together collections of aggregated DR assets and selling them to the grid as a single resource. However, in most cases these aggregated resources are not automated and when they are, they typically use proprietary technologies. There is a need for a framework for dealing with aggregated resources that supports the following requirements: • Allows demand-side resources to participate in multiple DR markets ranging from wholesale ancillary services to retail tariffs without being completely committed to a single entity like an Aggregator; • Allow aggregated groups of demand-side resources to be formed in an ad hoc fashion to address specific grid-side issues and support the optimization of the collective response of an aggregated group along a number of different dimensions. This is important in order to taylor the aggregated performance envelope to the needs to of the grid; • Allow aggregated groups to be formed in a hierarchical fashion so that each group can participate in variety of markets from wholesale ancillary services to distribution level retail tariffs. This paper explores the issues of aggregated groups of DR resources as described above especially within the context of emerging smart grid standards and the role they will play in both the management and interaction of various grid-side entities with those resources.

Implementation Proposal for The National Action Plan on Demand Implementation Proposal for The National Action Plan on DemandResponse Implementation Proposal for The National Action Plan on DemandResponse August 1, 2011 - 3:54pm Addthis EXECUTIVE SUMMARY The staff of the Federal Energy Regulatory Commission (FERC) and the U.S. Department of Energy (DOE) developed this implementation proposal as required by section 529 of the Energy Independence and Security Act of 2007 (EISA).1 In particular, this proposal complies with EISA's mandate "to submit to Congress a proposal to implement the [National] Action Plan [on DemandResponse], including specific proposed assignments of responsibility, proposed budget amounts, and any agreements secured for participation from State and other participants."2 The objective of the proposal is to implement the National Action Plan to

This paper discusses the specific concept for, design of, and results from a pilot program to automate demandresponse with critical peak pricing. California utilities have been exploring the use of critical peak pricing (CPP) to help reduce peak...

Recently due to major changes in the structure of electricity industry and the rising costs of power generation, many countries have realized the potential and benefits of smart metering systems and demandresponse

Abstract With the increasing integration of renewable energies into electrical grids, power imbalance has become one of the most critical issues in grid operations. The end-users at power demand side can actually make use of their demand reduction potentials to contribute to the grid power balance. Conventional demandresponses of end-users can provide considerable power demand reductions, but the demandresponses are usually subject to significant delay and cannot fulfill the needs of grid real time operation. In this paper, a fast chiller power demandresponse control strategy for commercial buildings is therefore proposed which facilitates buildings to act as grid “operating reserves” by providing rapid demandresponses to grid request within minutes. However, simply shutting down some essential operating chillers would result in disordered chilled water flow distribution and uneven indoor thermal comfort degradation. This strategy has therefore taken essential measures to solve such problems effectively. Simulation case studies are conducted to investigate the operation dynamics and energy performance of HVAC systems in the demandresponse events controlled by the strategy. Results show that fast and significant power demand reductions can be achieved without sacrificing the thermal comfort too much.

Abstract This paper proposes a new framework in which demandresponse (DR) is incorporated as an energy resource of electricity retailers in addition to the commonly used forward contracts and pool markets. In this way, a stepwise reward-based DR is proposed as a real-time resource of the retailer. In addition, the unpredictable behavior of customers participating in the proposed reward-based DR is modeled through a scenario-based participation factor. The overall problem is formulated as a stochastic optimization approach in which pool prices and customers’ participation in DR are uncertain variables. The feasibility of the problem is evaluated on a realistic case of the Australian National Electricity Market (NEM) and solved using General Algebraic Modeling System (GAMS) software.

In designing default service for competitive retail markets, demandresponse has been an afterthought at best. But that may be changing, as states that initiated customer choice in the past five to seven years reach an important juncture in retail market design and consider an RTP-type default service for large commercial and industrial customers. The authors describe the experience to date with RTP as a default service, focusing on its role as an instrument for cultivating price-responsivedemand. (author)

Abstract Developing countries constantly face the challenge of reliably matching electricity supply to increasing consumer demand. The traditional policy decisions of increasing supply and reducing demand centrally, by building new power plants and/or load shedding, have been insufficient. Locally installed microgrids along with consumer demandresponse can be suitable decentralized options to augment the centralized grid based systems and plug the demand–supply gap. The objectives of this paper are to: (1) develop a framework to identify the appropriate decentralized energy options for demand–supply matching within a community, and, (2) determine which of these options can suitably plug the existing demand–supply gap at varying levels of grid unavailability. A scenario analysis framework is developed to identify and assess the impact of different decentralized energy options at a community level and demonstrated for a typical urban residential community – Vijayanagar, Bangalore in India. A combination of LPG based CHP microgrid and proactive demandresponse by the community is the appropriate option that enables the Vijayanagar community to meet its energy needs 24/7 in a reliable, cost-effective manner. The paper concludes with an enumeration of the barriers and feasible strategies for the implementation of community microgrids in India based on stakeholder inputs.

The paper describes the demandresponse programs developed and in operation in New England, and the revised designs for participation in the forward capacity market. This description will include how energy efficiency, demand-side resources, and distributed generation are eligible to participate in this new forward capacity market. The paper will also discuss various methods that can be used to configure and communicate with demandresponse resources and important concerns in specifying interfaces that accommodate multiple technologies and allow technology choice and evolution.

This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demandresponse (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated DemandResponse (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.

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This report summarizes the Lawrence Berkeley National Laboratory's research to date in characterizing energy efficiency and open automated demandresponse opportunities for industrial refrigerated warehouses in California. The report describes refrigerated warehouses characteristics, energy use and demand, and control systems. It also discusses energy efficiency and open automated demandresponse opportunities and provides analysis results from three demandresponse studies. In addition, several energy efficiency, load management, and demandresponsecase studies are provided for refrigerated warehouses. This study shows that refrigerated warehouses can be excellent candidates for open automated demandresponse and that facilities which have implemented energy efficiency measures and have centralized control systems are well-suited to shift or shed electrical loads in response to financial incentives, utility bill savings, and/or opportunities to enhance reliability of service. Control technologies installed for energy efficiency and load management purposes can often be adapted for open automated demandresponse (OpenADR) at little additional cost. These improved controls may prepare facilities to be more receptive to OpenADR due to both increased confidence in the opportunities for controlling energy cost/use and access to the real-time data.

DemandResponse Opportunities and Enabling Technologies for Data Centers: DemandResponse Opportunities and Enabling Technologies for Data Centers: Findings From Field Studies Title DemandResponse Opportunities and Enabling Technologies for Data Centers: Findings From Field Studies Publication Type Report LBNL Report Number LBNL-5763E Year of Publication 2012 Authors Ghatikar, Girish, Venkata Ganti, Nance Matson, and Mary Ann Piette Publisher PG&E/SDG&E/CEC/LBNL Keywords communication and standards, control systems, data centers, demandresponse, enabling technologies, end-use technologies, load migration, market sectors, technologies Abstract The energy use in data centers is increasing and, in particular, impacting the data center energy cost and electric grid reliability during peak and high price periods. As per the 2007 U.S. Environmental Protection Agency (EPA), in the Pacific Gas and Electric Company territory, data centers are estimated to consume 500 megawatts of annual peak electricity. The 2011 data confirm the increase in data center energy use, although it is slightly lower than the EPA forecast. Previous studies have suggested that data centers have significant potential to integrate with supply-side programs to reduce peak loads. In collaboration with California data centers, utilities, and technology vendors, this study conducted field tests to improve the understanding of the demandresponse opportunities in data centers. The study evaluated an initial set of control and load migration strategies and economic feasibility for four data centers. The findings show that with minimal or no impact to data center operations a demand savings of 25% at the data center level or 10% to 12% at the whole building level can be achieved with strategies for cooling and IT equipment, and load migration. These findings should accelerate the grid-responsiveness of data centers through technology development, integration with the demandresponse programs, and provide operational cost savings.

Abstract DemandResponse mechanisms serve to preserve the stability of the power grid by shedding the electricity load of the consumers during power shortage situations in order to match power generation to demand. Data centres have been identified as excellent candidates to participate in such mechanisms. Recently a novel supply demand agreement have been proposed to foster power adaptation collaboration between energy provider and data centres. In this paper, we analyse the contractual terms of this agreement by proposing and studying different data centres’ power profile selecting policies. To this end, we setup a discrete event simulation and analysed the power grid’s state of a German energy provider. We believe that our analysis provides insight and knowledge for any energy utility in setting up the corresponding demand supply agreements.

Abstract In 2012 there was approximately 2400 electric vehicle DC Fast Charging stations sold globally. According to Pike Research (Jerram and Gartner, 2012), it is anticipated that by 2020 there will be approximately 460,000 of them installed worldwide. A typical public DC fast charger delivers a maximum power output of 50 kW which allows a typical passenger vehicle to be 80% charged in 10–15 min, compared with 6–8 h for a 6.6 kW AC level 2 charging unit. While DC fast chargers offer users the convenience of being able to rapidly charge their vehicle, the unit's high power demand has the potential to put sudden strain on the electricity network, and incur significant demand charges. Depending on the utility rate structure, a DC fast charger can experience annual demand charges of several thousand dollars. Therefore in these cases there is an opportunity to mitigate or even avoid the demand charges incurred by coupling the unit with an appropriately sized energy storage system and coordinating the way in which it integrates. This paper explores the technical and economical suitability of coupling a ground energy storage system with a DC fast charge unit for mitigation or avoidance of demand charges and lessening the impact on the local electricity network. This paper also discusses the concept of having the system participate in demandresponse programs in order to provide grid support and to further improve the economic suitability of an energy storage system.

Demandresponse is becoming a promising field of study ... . More attention has recently been paid to demandresponse programs. Customers can contribute to the operation of power systems by deployment demandresponse

Sixth Northwest Conservation and Electric Power Plan Chapter 5: DemandResponse Summary of Key.............................................................................................................. 1 DemandResponse in the Fifth Power Plan........................................................................................... 3 DemandResponse in the Sixth Power Plan

Opportunities for Energy Efficiency and DemandResponse in the California Opportunities for Energy Efficiency and DemandResponse in the California Cement Industry Title Opportunities for Energy Efficiency and DemandResponse in the California Cement Industry Publication Type Report LBNL Report Number LBNL-4849E Year of Publication 2010 Authors Olsen, Daniel, Sasank Goli, David Faulkner, and Aimee T. McKane Date Published 12/2010 Publisher CEC/LBNL Keywords cement industry, cement sector, demandresponse, electricity use, energy efficiency, market sectors, mineral manufacturing, technologies Abstract This study examines the characteristics of cement plants and their ability to shed or shift load to participate in demandresponse (DR). Relevant factors investigated include the various equipment and processes used to make cement, the operational limitations cement plants are subject to, and the quantities and sources of energy used in the cement-making process. Opportunities for energy efficiency improvements are also reviewed. The results suggest that cement plants are good candidates for DR participation. The cement industry consumes over 400 trillion Btu of energy annually in the United States, and consumes over 150 MW of electricity in California alone. The chemical reactions required to make cement occur only in the cement kiln, and intermediate products are routinely stored between processing stages without negative effects. Cement plants also operate continuously for months at a time between shutdowns, allowing flexibility in operational scheduling. In addition, several examples of cement plants altering their electricity consumption based on utility incentives are discussed. Further study is needed to determine the practical potential for automated demandresponse (Auto-DR) and to investigate the magnitude and shape of achievable sheds and shifts.

Jointly Optimizing Cost, Service, and Environmental Performance in Demand-Responsive Transit-cycle environmental consequences in vehicle routing and scheduling, which we develop for a demand- responsive

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A Successful Case Study of Small Business Energy Efficiency and Demand A Successful Case Study of Small Business Energy Efficiency and DemandResponse with Communicating Thermostats Jump to: navigation, search Tool Summary LAUNCH TOOL Name: A Successful Case Study of Small Business Energy Efficiency and DemandResponse with Communicating Thermostats Focus Area: Energy Efficiency Topics: Socio-Economic Website: drrc.lbl.gov/sites/drrc.lbl.gov/files/lbnl-2743e.pdf Equivalent URI: cleanenergysolutions.org/content/successful-case-study-small-business- Language: English Policies: Financial Incentives This report presents the results of a pilot study of 78 small commercial customers in the Sacramento Municipal Utility District. Participants were given a participation incentive and provided with both help in implementing energy efficiency measures for their buildings and an array of energy

? Would it be more effective if the consumer were to be part of the efficiency process? What about if the energy savings could be passed on to the consumer directly depending on how efficient he was? Demandresponse is a mechanism by which consumers change...

Microgrid (MG) is one of the important blocks in the future smart distribution systems. The scheduling pattern of MGs affects distribution system operation. Also the optimal scheduling of MGs will result in reliable and economical operation of distribution system. In this paper an operational planning model of a MG which considers multiple demandresponse programs is proposed. In the proposed approach all types of loads can participate in demandresponse programs which will be considered in either energy or reserve scheduling. Also the renewable distributed generation uncertainty is covered by reserve provided by both Distributed Generations (DGs) and responsive loads. The novelty of this paper is the demand side participation in energy and reserve scheduling simultaneously. Furthermore the energy and reserve scheduling is proposed for day-ahead and real-time. The proposed model was tested on a typical MG system and the results show that running demandresponse programs will reduce total operation cost of MG and cause more efficient use of resources.

Abstract— Demandresponse (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demandresponse implementation. Index Terms— Centralized control, decentralized control, demandresponse, electrical water heater, smart grid

1 Stackelberg Game based DemandResponse for At-Home Electric Vehicle Charging Sung-Guk Yoon Member, which is called demandresponse. Under demandresponse, retailers determine their electricity prices cost solution and the result of the equal- charging scheme. Index Terms--demandresponse, electric

Technology Demonstration Project for Small and Technology Demonstration Project for Small and Medium Commercial Buildings Title Automated DemandResponse Technology Demonstration Project for Small and Medium Commercial Buildings Publication Type Report LBNL Report Number LBNL-4982E Year of Publication 2011 Authors Page, Janie, Sila Kiliccote, Junqiao Han Dudley, Mary Ann Piette, Albert K. Chiu, Bashar Kellow, Edward Koch, and Paul Lipkin Date Published 07/2011 Publisher CEC/LBNL Keywords demandresponse, emerging technologies, market sectors, medium commercial business, openadr, small commercial, small commercial business, technologies Abstract Small and medium commercial customers in California make up about 20-25% of electric peak load in California. With the roll out of smart meters to this customer group, which enable granular measurement of electricity consumption, the investor-owned utilities will offer dynamic prices as default tariffs by the end of 2011. Pacific Gas and Electric Company, which successfully deployed Automated DemandResponse (AutoDR) Programs to its large commercial and industrial customers, started investigating the same infrastructures application to the small and medium commercial customers. This project aims to identify available technologies suitable for automating demandresponse for small-medium commercial buildings; to validate the extent to which that technology does what it claims to be able to do; and determine the extent to which customers find the technology useful for DR purpose. Ten sites, enabled by eight vendors, participated in at least four test AutoDR events per site in the summer of 2010. The results showed that while existing technology can reliably receive OpenADR signals and translate them into pre-programmed response strategies, it is likely that better levels of load sheds could be obtained than what is reported here if better understanding of the building systems were developed and the DR response strategies had been carefully designed and optimized for each site.

Abstract Power demandresponse is considered as one of the most promising solutions in relieving the power imbalance of an electrical grid that results a series of critical problems to the gird and end-users. In order to effectively make use of the demandresponse potentials of buildings, this paper presents a novel air-conditioning system with proactive demand control for daily load shifting and real time power balance in the developing smart grid. This system consists of a chilled water storage system (CWS) and a temperature and humidity independent control (THIC) air-conditioning system, which can significantly reduce the storage volume of the chilled water tank and effectively enable a building with more flexibility in changing its electricity usage patterns. The power demand of the proposed air-conditioning system can be flexibly controlled as desired by implementing two types of demandresponse strategies: demand side bidding (DSB) strategy and demand as frequency controlled reserve (DFR) strategy, in respond to the day-ahead and hour-ahead power change requirements of the grid, respectively. Considerable benefits (e.g., energy and cost savings) can be achieved for both the electricity utilities and building owners under incentive pricing or tariffs. A case study is conducted in a simulation platform to demonstrate the application of the proposed system in an office building.

Center (DRRC) at LBNL and New York State Energy Research andfunded by the New York State Energy Research and Developmentenergy efficiency and demandresponse: Framework concepts and a new construction study case in New York.

Demandresponse (DR) extends customer participation to power systems and results in a paradigm shift from simplex to interactive operation in power systems due to the advancement of smart grid technology. Therefore, it is important to model the customer characteristics in DR. This paper proposes customer information as the registration and participation information of DR, thus providing indices for evaluating customer response, such as DR magnitude, duration, frequency and marginal cost. The customer response characteristics are modeled from this information. This paper also introduces the new concept of virtual generation resources, whose marginal costs are calculated in the same manner as conventional generation marginal costs, according to customer information. Finally, some of the DR constraints are manipulated and expressed using the information modeled in this paper with various status flags. Optimal scheduling, combined with generation and DR, is proposed by minimizing the system operation cost, including generation and DR costs, with the generation and DR constraints developed in this paper.

Optimized HVAC Management Service to Enhance DemandResponse Optimized HVAC Management Service to Enhance DemandResponse Speaker(s): John Steinberg Date: August 18, 2011 - 12:00pm Location: 90-4133 Seminar Host/Point of Contact: Janie Page Many utilities are investing vast sums deploying smart meters to customers, some of whom remain stubbornly opposed to those deployments, in large part because they remain unmoved by the claimed benefits. EcoFactor has developed a thermostat management service that delivers (and quantifies) significant energy savings for consumers and a number of additional benefits to other players in the energy value chain. It does so without relying on consumers to modify behavior, study energy information displays, or even pay attention to their energy use. EcoFactor also significantly boosts DR yield while it increases occupant comfort. It can identify HVAC

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Demandresponse has grown to be a part of the repertoire of resources used by utilities to manage the balance between generation and load. In recent years, advances in communications and control technology have enabled utilities to consider continuously controlling demandresponse to meet generation, rather than the other way around. This paper discusses the economic applications of a general method for load resource analysis that parallels the approach used to analyze generation resources and uses the method to examine the results of the US Department of Energy’s Olympic Peninsula Demonstration Testbed. A market-based closed-loop system of controllable assets is discussed with necessary and sufficient conditions on system controllability, observability and stability derived.

or air-side economizers can be used in some data centers toair-cooled chillers and might have a water-side economizer. Few data centersdata center DR strategies using case studies and technologies for water or air-side economizers,

Real-Time DemandResponse with Uncertain Renewable Energy in Smart Grid Libin Jiang and Steven Low manages user load through real-time demandresponse and purchases balancing power on the spot market and demandresponse in the presence of uncertain renewable supply and time-correlated demand. The overall

DemandResponse Design based on a Stackelberg Game in Smart Grid Sung-Guk Yoon, Young-June Choi- time demandresponse can be applied. A smart grid network consisting of one retailer and many customers, demandresponse (DR) [3] is an indirect way to control the demand through hourly pricing information

HVAC units are currently one of the major resources providing demandresponse (DR) in residential buildings. Models of HVAC with DR function can improve understanding of its impact on power system operations and facilitate the deployment of DR technologies. This paper investigates the importance of various physical parameters and their distributions to the HVAC response to DR signals, which is a key step to the construction of HVAC models for a population of units with insufficient data. These parameters include the size of floors, insulation efficiency, the amount of solid mass in the house, and efficiency of the HVAC units. These parameters are usually assumed to follow Gaussian or Uniform distributions. We study the effect of uncertainty in the chosen parameter distributions on the aggregate HVAC response to DR signals, during transient phase and in steady state. We use a quasi-Monte Carlo sampling method with linear regression and Prony analysis to evaluate sensitivity of DR output to the uncertainty in the distribution parameters. The significance ranking on the uncertainty sources is given for future guidance in the modeling of HVAC demandresponse.

The Lawrence Berkeley National Laboratory (LBNL) DemandResponse Research Center (DRRC) demonstrated and evaluated open automated demandresponse (OpenADR) communication infrastructure to reduce winter morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA) in the Seattle City Light (SCL) service territory at five sites: Seattle Municipal Tower, Seattle University, McKinstry, and two Target stores. This report describes the process and results of the demonstration. OpenADR is an information exchange model that uses a client-server architecture to automate demand-response (DR) programs. These field tests evaluated the feasibility of deploying fully automated DR during both winter and summer peak periods. DR savings were evaluated for several building systems and control strategies. This project studied DR during hot summer afternoons and cold winter mornings, both periods when electricity demand is typically high. This is the DRRC project team's first experience using automation for year-round DR resources and evaluating the flexibility of commercial buildings end-use loads to participate in DR in dual-peaking climates. The lessons learned contribute to understanding end-use loads that are suitable for dispatch at different times of the year. The project was funded by BPA and SCL. BPA is a U.S. Department of Energy agency headquartered in Portland, Oregon and serving the Pacific Northwest. BPA operates an electricity transmission system and markets wholesale electrical power at cost from federal dams, one non-federal nuclear plant, and other non-federal hydroelectric and wind energy generation facilities. Created by the citizens of Seattle in 1902, SCL is the second-largest municipal utility in America. SCL purchases approximately 40% of its electricity and the majority of its transmission from BPA through a preference contract. SCL also provides ancillary services within its own balancing authority. The relationship between BPA and SCL creates a unique opportunity to create DR programs that address both BPA's and SCL's markets simultaneously. Although simultaneously addressing both market could significantly increase the value of DR programs for BPA, SCL, and the end user, establishing program parameters that maximize this value is challenging because of complex contractual arrangements and the absence of a central Independent System Operator or Regional Transmission Organization in the northwest.

Demandresponse (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind an solar power generation. However, DR in grid models is limited by data availability and modeling complexity. This presentation focuses on the co-optimization of DR resources to provide energy and ancillary services in a production cost model of the Colorado test system. We assume each DR resource can provide energy services by either shedding load or shifting its use between different times, as well as operating

This paper presents a preliminary framework to describe how advanced controls can support multiple modes of operations including both energy efficiency and demandresponse (DR). A general description of DR, its benefits, and nationwide status is outlined. The role of energy management and control systems for DR is described. Building systems such as HVAC and lighting that utilize control technologies and strategies for energy efficiency are mapped on to DR and demand shedding strategies are developed. Past research projects are presented to provide a context for the current projects. The economic case for implementing DR from a building owner perspective is also explored.

steel and glass. Pins, glass beads and headers are assembled manually and are put in a carbon tray. Carbon trays are put in furnaces (ovens) which are maintained at a constant temperature between 160Q-2000F and have an exothermic gas environment.... At this time, company registers its peak demand. Company keeps all furnaces on and keep them available for workers in case they will need it for their products. On average, no more than two furnaces will have same temperature and exothermic gas...

of price response (price elasticity of demand, substitutionprice elasticities, for estimating the market potential of demand responsedemand response market potential that account for customer behavior and prices through the use of price elasticities (

Sample records for demand response case from the National Library of Energy Beta (NLEBeta)

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A Cheat-Proof Game Theoretic DemandResponse Scheme for Smart Grids Yan Chen, W. Sabrina Lin, Feng}@umd.edu Abstract--While demandresponse has achieved promising results on making the power grid more efficient and reliable, the additional dynamics and flexibility brought by demandresponse also increase the uncertainty

Impact of Competition on Quality of Service in DemandResponsive Transit Ferdi Grootenboers1@inrets.fr Abstract. Demandresponsive transportation has the potential to pro- vide efficient public door-company, quality of service, auction 1 Introduction Demand-Responsive Transit (DRT) services are a form

A Privacy-Aware Architecture For DemandResponse Systems Stephen Wicker, Robert Thomas School architectures that realize the benefits of demandresponse without requiring that AMI data be centrally-based demandresponse efforts in the face of public outcry. We also show that Trusted Platform Modules can

Reduced-Order Modeling of Aggregated Thermostatic Loads With DemandResponse Wei Zhang, Jianming Lian, Chin-Yao Chang, Karanjit Kalsi and Yannan Sun Abstract-- DemandResponse is playing population of appliances under demandresponse is especially important to evaluate the effec- tiveness

A MODEL FOR THE FLEET SIZING OF DEMANDRESPONSIVE TRANSPORTATION SERVICES WITH TIME WINDOWS Marco a demandresponsive transit service with a predetermined quality for the user in terms of waiting time models; Continuous approximation models; Paratransit services; Demandresponsive transit systems. #12;3 1

1 Aggregated Modeling and Control of Air Conditioning Loads for DemandResponse Wei Zhang, Member, IEEE Abstract--Demandresponse is playing an increasingly impor- tant role in the efficient loads is especially important to evaluate the effec- tiveness of various demandresponse strategies

(2013) 1Â­28 Data Center DemandResponse: Avoiding the Coincident Peak via Workload Shifting.chen@hp.com Abstract Demandresponse is a crucial aspect of the future smart grid. It has the potential to provide centers' participation in demandresponse is becoming increasingly important given their high

to accurately estimate the transients caused by demandresponse is especially important to analyze the stability of the system under different demandresponse strategies, where dynamics on time scales of seconds to minutes demandresponse. The aggregated model efficiently includes statistical information of the population

Towards Building an Optimal DemandResponse Framework for DC Distribution Networks Hamed Mohsenian, an optimization-based foundation is proposed for demandresponse in DC distribution networks in presence to assess the performance and to gain insights into the proposed demand-response paradigm. Keywords: DC

Quantifying Benefits of DemandResponse and Look-ahead Dispatch in Systems with Variable Resources Electric Energy System #12;#12;Quantifying Benefits of DemandResponse and Look-ahead Dispatch in Systems benefits correspond to a real-world power system, as we use actual data on demand-response and wind

Design and Valuation of DemandResponse Mechanisms and Instruments for Integrating Renewable) research project titled "Design and Valuation of DemandResponse Mechanisms and Instruments for Integrating resources. The increased reserve requirement can be met using the so-called demandresponse resources (DRRs

A Multi-Resolution Large Population Game Framework for Smart Grid DemandResponse Management Quanyan Zhu and Tamer BasÂ¸ar Abstract--Dynamic demandresponse (DR) management is becoming an integral, active operation, and efficient demandresponse. A reliable and efficient communication and networking

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The integration of demandresponse resources into wholesale electricity markets facilitates the growth in wind power integration. Available demand resources have different capabilities in terms of response time, as demonstrated by the variety of programs ... Keywords: demandresponse, wind integration, power spectral density

State and Regional Policy Assistance Â» Technical Assistance Â» Demand State and Regional Policy Assistance Â» Technical Assistance Â» DemandResponse - Policy Â» A National Forum on DemandResponse: What Remains to Be Done to Achieve Its Potential A National Forum on DemandResponse: What Remains to Be Done to Achieve Its Potential In July 2011, the Federal Energy Regulatory Commission's (FERC) staff and the Department of Energy (DOE) jointly submitted to Congress a required "Implementation Proposal for the National Action Plan on DemandResponse." The Implementation Proposal was for FERC's June 2010 National Action Plan for DemandResponse. Part of the July 2011 Implementation Proposal called for a "National Forum" on demandresponse to be conducted by DOE and FERC. Given the rapid development of the demandresponse industry, DOE and FERC decided

The Issue Demand-response (DR) programs, in which facilities reduce their electric loads (Figure 1). The testing covered four Lighting the Way to DemandResponseLighting the Way to DemandResponse California Energy Commission's Public Interest Energy Research Program Technical Brief PIER

This paper describes a framework for analyzing the imperfect price-reversibility (hysteresis) of oil demand. The oil demand reductions following the oil price increases of the 1970s will not be completely reversed by the price cuts of the 1980s, nor is it necessarily true that these partial demand reversals themselves will be reversed exactly by future price increases. The author decomposes price into three monotonic series: price increases to maximum historic levels, price cuts, and price recoveries (increases below historic highs). He would expect that the response to price cuts would be no greater than to price recoveries, which in turn would be no greater than for increases in maximum historic price. For evidence of imperfect price-reversibility, he tests econometrically the following US data: vehicle miles per driver, the fuel efficiency of the automobile fleet, and gasoline demand per driver. In each case, the econometric results allow him to reject the hypothesis of perfect price-reversibility. The data show smaller response to price cuts than to price increases. This has dramatic implications for projections of gasoline and oil demand, especially under low-price assumptions. 26 refs., 13 figs., 3 tabs.

In 2006 the DemandResponse Research Center (DRRC) formed an Industrial DemandResponse Team to investigate opportunities and barriers to implementation of Automated DemandResponse (Auto-DR) systems in California industries. Auto-DR is an open, interoperable communications and technology platform designed to: Provide customers with automated, electronic price and reliability signals; Provide customers with capability to automate customized DR strategies; Automate DR, providing utilities with dispatchable operational capability similar to conventional generation resources. This research began with a review of previous Auto-DR research on the commercial sector. Implementing Auto-DR in industry presents a number of challenges, both practical and perceived. Some of these include: the variation in loads and processes across and within sectors, resource-dependent loading patterns that are driven by outside factors such as customer orders or time-critical processing (e.g. tomato canning), the perceived lack of control inherent in the term 'Auto-DR', and aversion to risk, especially unscheduled downtime. While industry has demonstrated a willingness to temporarily provide large sheds and shifts to maintain grid reliability and be a good corporate citizen, the drivers for widespread Auto-DR will likely differ. Ultimately, most industrial facilities will balance the real and perceived risks associated with Auto-DR against the potential for economic gain through favorable pricing or incentives. Auto-DR, as with any ongoing industrial activity, will need to function effectively within market structures. The goal of the industrial research is to facilitate deployment of industrial Auto-DR that is economically attractive and technologically feasible. Automation will make DR: More visible by providing greater transparency through two-way end-to-end communication of DR signals from end-use customers; More repeatable, reliable, and persistent because the automated controls strategies that are 'hardened' and pre-programmed into facility's software and hardware; More affordable because automation can help reduce labor costs associated with manual DR strategies initiated by facility staff and can be used for long-term.

In 2006, the Public Interest Energy Research Program (PIER) DemandResponse Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated DemandResponse (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This ?electricity value chain? defines energy management and demandresponse (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demandresponse. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to"demo" potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives.1 In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies of refrigerated warehouses and wastewater treatment facilities are used to illustrate OpenADR load reduction potential. Typical shed and shift strategies include: turning off or operating compressors, aerator blowers and pumps at reduced capacity, increasing temperature set-points or pre-cooling cold storage areas and over-oxygenating stored wastewater prior to a DR event. This study concludes that understanding industrial end-use processes and control capabilities is a key to support reduced service during DR events and these capabilities, if DR enabled, hold significant promise in reducing the electricity demand of the industrial sector during utility peak periods.

Abstract DR (Demandresponse) measures typically aim at an improved utilization of power plant and grid capacities. In energy systems mainly relying on photovoltaic and wind power, DR may furthermore contribute to system stability and increase the renewable energy share. In this paper, an assessment of the theoretical DR potential in Europe is presented. Special attention is given to temporal availability and geographic distribution of flexible loads. Based on industrial production and electricity consumption statistics, as well as periodic and temperature-dependent load profiles, possible load reduction and increase is estimated for each hour of the year. The analysis identifies substantial DR potentials in all consumer sectors. They add up to a minimum load reduction of 61 GW and a minimum load increase of 68 GW, available in every hour of the year. The overall potential features significant variations during the year, which are characteristic for specific consumers and countries.

Demandresponse (DR) resources present a potentially important source of grid flexibility particularly on future systems with high penetrations of variable wind and solar power generation. However, managed loads in grid models are limited by data availability and modeling complexity. This presentation focuses on the value of co-optimized DR resources to provide energy and ancillary services in a production cost model. There are significant variations in the availabilities of different types of DR resources, which affect both the operational savings as well as the revenue for each DR resource. The results presented include the system-wide avoided fuel and generator start-up costs as well as the composite revenue for each DR resource by energy and operating reserves. In addition, the revenue is characterized by the capacity, energy, and units of DR enabled.

A National Forum on DemandResponse: Results on What Remains to Be A National Forum on DemandResponse: Results on What Remains to Be Done to Achieve Its Potential - Tools and Methods Working Group A National Forum on DemandResponse: Results on What Remains to Be Done to Achieve Its Potential - Tools and Methods Working Group In July 2011, the Federal Energy Regulatory Commission's (FERC) staff and the Department of Energy (DOE) jointly submitted to Congress a required "Implementation Proposal for the National Action Plan on DemandResponse." The Implementation Proposal was for FERC's June 2010 National Action Plan for DemandResponse. Part of the July 2011 Implementation Proposal called for a "National Forum" on demandresponse to be conducted by DOE and FERC. Given the rapid development of the demandresponse industry, DOE and FERC decided

This paper describes the concept for and lessons from the development and field-testing of an open, interoperable communications infrastructure to support automated demandresponse (auto-DR). Automating DR allows greater levels of participation, improved reliability, and repeatability of the DR in participating facilities. This paper also presents the technical and architectural issues associated with auto-DR and description of the demandresponse automation server (DRAS), the client/server architecture-based middle-ware used to automate the interactions between the utilities or any DR serving entity and their customers for DR programs. Use case diagrams are presented to show the role of the DRAS between utility/ISO and the clients at the facilities.

The consumers try to obtain their electricity demand at minimum cost from different resources in restructured electricity markets. Hence more attention have been made on demandresponse programs (DRP) which aims ...

Calls to improve customer participation as a key element of smart grids have reinvigorated interest in demand-side features such as distributed generation, on-site storage and demandresponse. In the context of deregulated ...

Smart grid is a recently growing area of research including optimum and reliable operation of bulk power grid from production to end-user premises. Demand side activities like demandresponse (DR) for enabling co...

Automated Price and DemandResponse Demonstration for Large Customers Automated Price and DemandResponse Demonstration for Large Customers in New York City using OpenADR T2 International Conference for Enhanced Building Operations ICEBO A1 Joyce Jihyun Kim A1 Rongxin Yin A1 Sila Kiliccote AB p class p1 Open Automated DemandResponse OpenADR an XML based information exchange model is used to facilitate continuous price responsive operation and demandresponse participation for large commercial buildings in New York who are subject to the default day ahead hourly pricing We summarize the existing demandresponse programs in New York and discuss OpenADR communication prioritization of demandresponse signals and control methods Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management

Using data for 1971–2008, we estimate the effects of changes in price and income on world oil demand, disaggregated by product – transport oil, fuel oil (residual and heating oil), and other oil – for six groups of countries. Most of the demand reductions since 1973–74 were due to fuel-switching away from fuel oil, especially in the OECD; in addition, the collapse of the Former Soviet Union (FSU) reduced their oil consumption substantially. Demand for transport and other oil was much less price-responsive, and has grown almost as rapidly as income, especially outside the OECD and FSU. World oil demand has shifted toward products and regions that are faster growing and less price-responsive. In contrast to projections to 2030 of declining per-capita demand for the world as a whole – by the U.S. Department of Energy (DOE), International Energy Agency (IEA) and OPEC – we project modest growth. Our projections for total world demand in 2030 are at least 20% higher than projections by those three institutions, using similar assumptions about income growth and oil prices, because we project rest-of-world growth that is consistent with historical patterns, in contrast to the dramatic slowdowns which they project.

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A National Forum on DemandResponse: Results on What Remains to Be A National Forum on DemandResponse: Results on What Remains to Be Done to Achieve Its Potential - Program Design and Implementation Working Group A National Forum on DemandResponse: Results on What Remains to Be Done to Achieve Its Potential - Program Design and Implementation Working Group In July 2011, the Federal Energy Regulatory Commission's (FERC) staff and the Department of Energy (DOE) jointly submitted to Congress a required "Implementation Proposal for the National Action Plan on DemandResponse." The Implementation Proposal was for FERC's June 2010 National Action Plan for DemandResponse. Part of the July 2011 Implementation Proposal called for a "National Forum" on demandresponse to be conducted by DOE and FERC. Given the

Action Plan on DemandResponse, June 2010 Action Plan on DemandResponse, June 2010 National Action Plan on DemandResponse, June 2010 The Federal Energy Regulatory Commission (FERC) is required to develop the National Action Plan on DemandResponse (National Action Plan) as outlined in section 529 of the Energy Independence and Security Act of 2007 (EISA), entitled "Electricity Sector DemandResponse." This National Action Plan is designed to meet three objectives: Identify "requirements for technical assistance to States to allow them to maximize the amount of demandresponse resources that can be developed and deployed." Design and identify "requirements for implementation of a national communications program that includes broad-based customer education and support."

Advanced metering constitutes an essential component of communications between electricity suppliers and consumers. It may be possible to augment demandresponse by coupling Advanced Metering Infrastructure (AMI)...

The penetration of wind power generation is expected to increase in power systems dramatically. The unpredictable nature of the wind generation poses an obstacle to high penetration of wind energy in the electric power systems. Demandresponse (DR) may be considered as an efficient approach to cope with the energy unbalances caused by the wind power intermittency. Fair mechanism for pricing of the DR may increase the demand-side participation which consequently facilitates wind power integration in the power systems. This paper focuses on the economic evaluation of the DR according to its potential for mitigating the wind power forecast error in the power system operation. Demand increase similar to the demand curtailment is considered as a DR resource and evaluated in this paper. For this purpose first an insight is provided into the power system operation under the high wind power penetration with the aim of extracting the DR benefits. Based on the DR benefits a mathematical model is developed to find the maximum monetary incentive for the DR that the system operator is willing to pay to the DR providers. In the proposed model DR's potential in reducing the cost of supplying load as well as its capability in reducing the cost of system reserve start up and shut down of units load shedding and wind power spillage are considered. The results of the proposed evaluation method provide valuable information for both the system operator and demandresponse providers. The proposed method is implemented on an example and a realistic case study and discussions on results are presented.

Recently issued U.S. Federal Energy Regulatory Commission regulations require comparable treatment of demand reduction and generation in the wholesale electric market so that they are compensated at the same mark...

Abstract The intermittent nature of the wind generation poses an obstacle to high penetration of wind energy in electric power systems. Demandresponse (DR) increases the flexibility of the power system by allowing very fast upward/downward changes in the demand. This potential can be interpreted as the ability to provide fast upward/downward reserves, facilitating the utilization of the wind power in the power system. Demandresponse exchange (DRX) market is a separate market in which DR is treated as a virtual resource to be exchanged between DR buyers and sellers. The major advantage of the DRX market in comparison to other DR proposals is that it allocates benefits and payments across all participants, fairly. However, there are still obstacles to its integration into the existing power markets. This paper proposes a short-term framework for DRX market that considers the interactions between the DRX market and energy/reserve markets. The proposed framework is aimed at reducing the operational costs incurred by the uncertainty of the wind power and providing a fair mechanism for valuation of the DR as a virtual resource. A stochastic programming model is used to clear the DRX market considering the wind power production scenarios. To illustrate the efficiency of the proposed DRX market framework, it is implemented on a simple and a realistic case study.

Design and efficiency of houses can affect the amount of peak load reduction available from a residential demandresponse program. Twenty-four houses were simulated with varying thermal integrity and air conditioner size during the summer cooling season ... Keywords: demandresponse, efficiency, residential, hvac, conservation

This poster presents latency and reliability characterization of wireless sensor network as applied to an advanced building control system for demandresponse energy pricing. A test network provided the infrastructure to extract round trip time and packet ... Keywords: advanced building control, demandresponse energy pricing

Supply Chain Networks with Global Outsourcing and Quick-Response Production Under Demand and Cost framework for supply chain networks with global outsourcing and quick-response production under demand University of Massachusetts Amherst, Massachusetts 01003 May 2011; revised September 2011 Annals

Cost-Effectiveness Working Group Cost-Effectiveness Working Group A National Forum on DemandResponse: Results on What Remains to Be Done to Achieve Its Potential - Cost-Effectiveness Working Group In July 2011, the Federal Energy Regulatory Commission's (FERC) staff and the Department of Energy (DOE) jointly submitted to Congress a required "Implementation Proposal for the National Action Plan on DemandResponse." The Implementation Proposal was for FERC's June 2010 National Action Plan for DemandResponse. Part of the July 2011 Implementation Proposal called for a "National Forum" on demandresponse to be conducted by DOE and FERC. Given the rapid development of the demandresponse industry, DOE and FERC decided that a "virtual" project, in which state officials, industry

Measurement and Verification Working Group Measurement and Verification Working Group A National Forum on DemandResponse: Results on What Remains to Be Done to Achieve Its Potential - Measurement and Verification Working Group In July 2011, the Federal Energy Regulatory Commission's (FERC) staff and the Department of Energy (DOE) jointly submitted to Congress a required "Implementation Proposal for the National Action Plan on DemandResponse." The Implementation Proposal was for FERC's June 2010 National Action Plan for DemandResponse. Part of the July 2011 Implementation Proposal called for a "National Forum" on demandresponse to be conducted by DOE and FERC. Given the rapid development of the demandresponse industry, DOE and FERC decided that a "virtual" project, in which state officials, industry

the DemandResponse and Smart Grid Coalition on DOE's the DemandResponse and Smart Grid Coalition on DOE's Implementing the National Broadband Plan by Empowering Consumers and the Smart Grid: Data Access, Third Party Use, and Privacy Comments of the DemandResponse and Smart Grid Coalition on DOE's Implementing the National Broadband Plan by Empowering Consumers and the Smart Grid: Data Access, Third Party Use, and Privacy The DemandResponse and Smart Grid Coalition (DRSG), the trade association for companies that provide products and services in the areas of demandresponse and smart grid technologies, respectfully submits its comments to the Department of Energy's Request for Information "Implementing the National Broadband Plan by Empowering Consumers and the Smart Grid: Data Access, Third Party Use, and Privacy."

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In this paper, we study supply and demand management in the presence of conventional and renewable energy sources, where the latter is represented by a single wind turbine. Total social welfare, defined in terms of consumer utility and cost of power ... Keywords: constrained optimization, kuhn-tucker conditions, outage probability, renewable source, smart grid

It has been widely accepted that demandresponse will play an important role in reliable and economic operation of future power systems and electricity markets. Demandresponse can not only influence the prices in the energy market by demand shifting, but also participate in the reserve market. In this paper, we propose a full model of demandresponse in which demand flexibility is fully utilized by price responsive shiftable demand bids in energy market as well as spinning reserve bids in reserve market. A co-optimized day-ahead energy and spinning reserve market is proposed to minimize the expected net cost under all credible system states, i.e., expected total cost of operation minus total benefit of demand, and solved by mixed integer linear programming. Numerical simulation results on the IEEE Reliability Test System show effectiveness of this model. Compared to conventional demand shifting bids, the proposed full demandresponse model can further reduce committed capacity from generators, starting up and shutting down of units and the overall system operating costs.

Demandresponse (DR) is an effective tool which resolves inconsistencies between electric power supply and demand. It further provides a reliable and credible resource that ensures stable and economical operation of the power grid. This paper introduces systematic definitions for DR and demand side management, along with operational differences between these two methods. A classification is provided for DR programs, and various DR strategies are provided for application in air conditioning and refrigerating systems. The reliability of DR is demonstrated through discussion of successful overseas examples. Finally, suggestions as to the implementation of demandresponse in China are provided.

DemandResponse: Lessons Learned with an Eye to the Future DemandResponse: Lessons Learned with an Eye to the Future DemandResponse: Lessons Learned with an Eye to the Future July 11, 2013 - 11:56am Addthis Patricia A. Hoffman Patricia A. Hoffman Assistant Secretary, Office of Electricity Delivery & Energy Reliability In today's world of limited resources and rising costs, everyone is looking for ways to use what they have more effectively while, at the same time, controlling - and ideally - reducing expenses. The electricity industry is no exception. Through demandresponse programs such as time-based rates in which customers are offered financial incentives to reduce or shift their consumption during peak periods, utilities are reducing demand and better managing their assets while also giving consumers more options and lowering the cost of electricity. For example,

Demandresponse is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demandresponse programs at various times. This paper focuses on developing aggregated control models for a population of thermostatically controlled loads. The effects of demandresponse on the load population dynamics are investigated.

Decentralized Control of Aggregated Loads for DemandResponse Di Guo, Wei Zhang, Gangfeng Yan of residential responsive loads for vari- ous demandresponse applications. We propose a general hybrid system and effectively reduce the peak power consumption. I. INTRODUCTION Demandresponse has the potential to shift

the 2004 Fully Automated DemandResponse Tests in Large the 2004 Fully Automated DemandResponse Tests in Large Facilities Title Findings from the 2004 Fully Automated DemandResponse Tests in Large Facilities Publication Type Report LBNL Report Number LBNL-58178 Year of Publication 2005 Authors Piette, Mary Ann, David S. Watson, Naoya Motegi, and Norman Bourassa Date Published 10/18/2005 Keywords market sectors, technologies Abstract This report describes the results of the second season of research to develop and evaluate the performance of new Automated DemandResponse (Auto-DR) hardware and software technology in large facilities. DemandResponse (DR) is a set of time dependant activities that reduce or shift electricity use to improve electric grid reliability, manage electricity costs, and provide systems that encourage load shifting or shedding during times when the electric grid is near its capacity or electric prices are high. DemandResponse is a subset of demand side management, which also includes energy efficiency and conservation. The overall goal of this research project was to support increased penetration of DR in large facilities through the use of automation and better understanding of DR technologies and strategies in large facilities. To achieve this goal, a set of field tests were designed and conducted. These tests examined the performance of Auto-DR systems that covered a diverse set of building systems, ownership and management structures, climate zones, weather patterns, and control and communication configurations.

Power systems are undergoing a paradigm shift due to the influx of variable renewable generation to the supply side. The resulting increased uncertainty has system operators looking to new resources, enabled by smart grid technologies, on the demand ... Keywords: demandresponse, inverse building model, load shedding, thermostatically controlled loads

Demandresponse (DR) is an important demand-side resource that allows for lower electricity consumption when the system is under stress. This paper presents a DR framework that can be implemented within a home area network, as well as a conceptual hardware ...

Comfort-Aware Home Energy Management Under Market-Based Demand-Response Jin Xiao, Jian Li, Raouf-based pricing. In peak capping, each home is allocated an energy quota. In market-based pricing, the price of energy varies based on market supply-demand. Market-based This research was supported by World Class

and Smart Metering Policy Actions Since the Energy and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials DemandResponse and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials This report represents a review of policy developments on demandresponse and other related areas such as smart meters and smart grid. It has been prepared by the DemandResponse Coordinating Committ ee (DRCC) for the National Council on Electricity Policy (NCEP). The report focuses on State and Federal policy developments during the period from 2005 to mid-year 2008. It is an att empt to catalogue information on policy developments at both the federal and state level, both in the legislative and regulatory arenas. DemandResponse and Smart Metering Policy Actions Since the Energy Policy

time interval of a new demandresponsive transit "feeder" service within one representative colonia, El Cenizo. A comprehensive analysis of the results of a survey conducted through a questionnaire is presented to explain the existing travel patterns...

Abstract The present study presents a new risk-constrained bidding strategy formulation of large electric utilities in, presence of demandresponse programs. The considered electric utility consists of generation facilities, along with a retailer part, which is responsible for supplying associated demands. The total profit of utility comes from participating in day-ahead energy markets and selling energy to corresponding consumers via retailer part. Different uncertainties, such as market price, affect the profit of the utility. Therefore, here, attempts are made to make use of Information Gap Decision Theory (IGDT) to obtain a robust scheduling method against the unfavorable deviations of the market prices. Implementing demandresponse programs sounds attractive for the consumers through providing some incentives in one hand, and it improves the risk hedging capability of the utility on the other hand. The proposed method is applied to a test system and effect of demandresponse programs is investigated on the total profit of the utility.

We introduce and analyze Markov Decision Process (MDP) machines to model individual devices which are expected to participate in future demand-response markets on distribution grids. We differentiate devices into the ...

Global Energy Partners provides a review of California’s strategic approach to energy efficiency and demandresponse implementation, with a focus on the industrial sector. The official role of the state, through the California Energy Commission (CEC...

This paper explores the feasibility of integrating energy efficiency program evaluation with the emerging need for the evaluation of programs from different “energy cultures” (demandresponse, renewable energy, a...

We describe and demonstrate a prototype software architecture to support data-driven demandresponse optimization (DR) in the USC campus microgrid, as part of the Los Angeles Smart Grid Demonstration Project. The architecture includes a semantic ...

Wind imposes costs on power systems due to uncertainty and variability of real-time resource availability. Stochastic programming and demandresponse are offered as two possible solutions to ... although both wil...

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This study investigated the ability of responsivedemand to stabilize the electrical grid when intermittent renewable resources are present. The WILMAR stochastic unit commitment model was used to represent a version of ...

This dissertation includes three essays on the causes and responses to shifts in demand for authenticity. In the first chapter, I answer the question: why do previously cast-off products, practices, or styles abruptly ...

Mass market demandresponse programmes may be utilised to assist bulk ... and software architecture in households. In contrast, demandresponse systems based only on information exchange between ... uptake. The e...

1 A Hierarchical DemandResponse Framework for Data Center Power Cost Optimization Under Real for optimizing their utility bills. Our focus is on a subset of this work that carries out demandresponse (DR

1 Abstract -- DemandResponse (DR) programs are not a new concept; moreover, the key technologies migrate to active and dynamic demandresponse, under reliability criteria based on the smart grid paradigm. This article formulates a new perspective of demandresponse in emerging countries, based on the US

Topic 4: DemandResponse A.H. MohsenianRad (U of T) 1Networking and Distributed Systems Department;Definition of DemandResponse Dr. Hamed Mohsenian-Rad Texas Tech UniversityCommunications and Control in Smart Grid Â· According to the U.S. Department of Energy: Demandresponse (DR) is defined as changes

for Responsive/Adaptive Load by Jason W. Black Massachusetts Institute of Technology Submitted to the Engineering integration of demandresponse. Integrating demand into the US electricity system will allow the development, and market issues to determine a system structure that provides incentives for demandresponse. An integrated

Abstract Smart grids play a key role in realizing climate ambitions. Boosting consumption flexibility is an essential measure in bringing the potential gains of smart grids to fruition. The collective scientific understanding of demandresponse programs argues that time-of-use tariffs have proven its merits. The findings upon which this conclusion rests are, however, primarily derived from studies covering energy-based time-of-use rates over fairly short periods of time. Hence, this empirical study set out with the intention of estimating the extent of response to a demand-based time-of-use electricity distribution tariff among Swedish single-family homes in the long term. The results show that six years after the implementation households still respond to the price signals of the tariff by cutting demand in peak hours and shifting electricity consumption from peak to off-peak hours. Studies conducted in the Nordic countries commonly include only homeowners and so another aim of the study was to explore the potential of demandresponse programs among households living in apartment buildings. The demand-based tariff proved to bring about similar, but not as marked, effects in rental apartments, whereas there are virtually no corresponding evidences of demandresponse in condominium apartments.

Supply Chain Networks with Global Outsourcing and Quick-Response Production Under Demand and Cost University of Massachusetts Amherst, Massachusetts 01003 May 2011 Abstract This paper develops a modeling and computational framework for supply chain networks with global outsourcing and quick-response production under

Frequency ResponsiveDemand Frequency ResponsiveDemand Jeff Dagle, PE Chief Electrical Engineer Advanced Power & Energy Systems Pacific Northwest National Laboratory (509) 375-3629 jeff.dagle@pnl.gov CERTS Project Meeting Berkeley, CA September 20, 2012 Acknowledgements Montana Tech University MK Donnelly DJ Turdnowski S Mattix 2 Project Objective This project is evaluating the utilization of large numbers of small loads to provide spinning reserve The specific scope of this project is comparing the ability of load to provide equivalent primary frequency response that would be available from conventional generation 3 Utilizing Small Loads for Frequency Responsive Reserves in a Large System Model Objectives: Credible analysis of the feasibility of using load as a frequency responsive

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Open Automated DemandResponse (OpenADR), an XML-based information exchange model, is used to facilitate continuous price-responsive operation and demandresponse participation for large commercial buildings in New York who are subject to the default day-ahead hourly pricing. We summarize the existing demandresponse programs in New York and discuss OpenADR communication, prioritization of demandresponse signals, and control methods. Building energy simulation models are developed and field tests are conducted to evaluate continuous energy management and demandresponse capabilities of two commercial buildings in New York City. Preliminary results reveal that providing machine-readable prices to commercial buildings can facilitate both demandresponse participation and continuous energy cost savings. Hence, efforts should be made to develop more sophisticated algorithms for building control systems to minimize customer's utility bill based on price and reliability information from the electricity grid.

DemandResponse is playing an increasingly important role in smart grid control strategies. Modeling the behavior of populations of appliances under demandresponse is especially important to evaluate the effectiveness of these demandresponse programs. In this paper, an aggregated model is proposed for a class of Thermostatically Controlled Loads (TCLs). The model efficiently includes statistical information of the population, systematically deals with heterogeneity, and accounts for a second-order effect necessary to accurately capture the transient dynamics in the collective response. However, an accurate characterization of the collective dynamics however requires the aggregate model to have a high state space dimension. Most of the existing model reduction techniques require the stability of the underlying system which does not hold for the proposed aggregated model. In this work, a novel model reduction approach is developed for the proposed aggregated model, which can significantly reduce its complexity with small performance loss. The original and the reducedorder aggregated models are validated against simulations of thousands of detailed building models using GridLAB-D, which is a realistic open source distribution simulation software. Index Terms – demandresponse, aggregated model, ancillary

In this paper an analytical study is reported to demonstrate the effects of demandresponse on distribution network voltages profile. Also a new approach for real time voltage control is proposed which uses emergency demandresponse program aiming at maintaining voltage profile in an acceptable range with minimum cost. This approach will be active in emergency conditions where in real time the voltages in some nodes leave their permissible ranges. These emergency conditions are Distributed Generation (DG) units and lines outage and unpredictable demand and renewable generations' fluctuations. The proposed approach does not need the load and renewable generation forecast data to regulate voltage. To verify the effectiveness and robustness of the proposed control scheme the proposed voltage control scheme is tested on a typical distribution network. The simulation results show the effectiveness and capability of the proposed real time voltage control model to maintain smart distribution network voltage in specified ranges in both normal and emergency conditions.

. In the face of potential abuse or other malice, it seems clear that future Internet designs need to addressAddressing Reality: An Architectural Response to Real-World Demands on the Evolving Internet David jtw@lcs.mit.edu Ted Faber USC ISI faber@isi.edu ABSTRACT A system as complex as the Internet can only

Electricity generation from wind power and other renewable energy sources is increasing, and their variability introduces new challenges to the power system. The emergence of smart grid technologies in recent years has seen a paradigm shift in redefining the electrical system of the future, in which controlled response of the demand side is used to balance fluctuations and intermittencies from the generation side. This paper presents a modeling framework for an integrated electricity system where loads become an additional resource. The agent-based model represents a smart grid power system integrating generators, transmission, distribution, loads and market. The model incorporates generator and load controllers, allowing suppliers and demanders to bid into a Real-Time Pricing (RTP) electricity market. The modeling framework is applied to represent a physical demonstration project conducted on the Olympic Peninsula, Washington, USA, and validation simulations are performed using actual dynamic data. Wind power is then introduced into the power generation mix illustrating the potential of demandresponse to mitigate the impact of wind power variability, primarily through thermostatically controlled loads. The results also indicate that effective implementation of DemandResponse (DR) to assist integration of variable renewable energy resources requires a diversity of loads to ensure functionality of the overall system.

This study analyzes the impact of the energy efficiency (EE) and demandresponse (DR) programs on the grid and the consequent level of production. Changes in demand caused by EE and DR programs affect not only the dispatch of existing plants and new generation technologies, the retirements of old plants, and the finances of the market. To find the new equilibrium in the market, we use the Oak Ridge Competitive Electricity Dispatch Model (ORCED) developed to simulate the operations and costs of regional power markets depending on various factors including fuel prices, initial mix of generation capacity, and customer response to electricity prices. In ORCED, over 19,000 plant units in the nation are aggregated into up to 200 plant groups per region. Then, ORCED dispatches the power plant groups in each region to meet the electricity demands for a given year up to 2035. In our analysis, we show various demand, supply, and dispatch patterns affected by EE and DR programs across regions.

discussions of the model in [79] and [80], and [81] for an application. 6 Developed by the Tennessee Valley Authority (TVA) and Oak Ridge National Laboratory (ORNL) of the United States of America [82]. EPRG No 1113 5 Planning (IRP) was developed.7... Integrating short-term demandresponse into long-term investment planning Cedric De Jonghe, Benjamin F. Hobbs and Ronnie Belmans 20 March 2011 CWPE 1132 & EPRG 1113 www.eprg.group.cam.ac.uk EP RG W...

This scoping study focuses on the policy issues inherent in the claims made by some Smart Grid proponents that the demandresponse potential of mass market customers which is enabled by widespread implementation of Advanced Metering Infrastructure (AMI) through the Smart Grid could be the “silver bullet” for mitigating variable generation integration issues. In terms of approach, we will: identify key issues associated with integrating large amounts of variable generation into the bulk power system; identify demandresponse opportunities made more readily available to mass market customers through widespread deployment of AMI systems and how they can affect the bulk power system; assess the extent to which these mass market DemandResponse (DR) opportunities can mitigate Variable Generation (VG) integration issues in the near-term and what electricity market structures and regulatory practices could be changed to further expand the ability for DR to mitigate VG integration issues over the long term; and provide a qualitative comparison of DR and other approaches to mitigate VG integration issues.

This report reviews the Open Automated DemandResponse (OpenADR) deployments within the territories serviced by California?s investor-owned utilities (IOUs) and the transition from the OpenADR 1.0 specification to the formal standard?OpenADR 2.0. As demandresponse service providers and customers start adopting OpenADR 2.0, it is necessary to ensure that the existing Automated DemandResponse (AutoDR) infrastructure investment continues to be useful and takes advantage of the formal standard and its many benefits. This study focused on OpenADR deployments and systems used by the California IOUs and included a summary of the OpenADR deployment from the U.S. Department of Energy-funded demonstration conducted by the Sacramento Municipal Utility District (SMUD). Lawrence Berkeley National Laboratory collected and analyzed data about OpenADR 1.0 deployments, categorized architectures, developed a data model mapping to understand the technical compatibility of each version, and compared the capabilities and features of the two specifications. The findings, for the first time, provided evidence of the total enabled load shed and average first cost for system enablement in the IOU and SMUD service territories. The OpenADR 2.0a profile specification semantically supports AutoDR system architectures and data propagation with a testing and certification program that promotes interoperability, scaled deployments by multiple vendors, and provides additional features that support future services.

Sample records for demand response case from the National Library of Energy Beta (NLEBeta)

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California is a leader in automating demandresponse (DR) to promote low-cost, consistent, and predictable electric grid management tools. Over 250 commercial and industrial facilities in California participate in fully-automated programs providing over 60 MW of peak DR savings. This paper presents a summary of Open Automated DR (OpenADR) implementation by each of the investor-owned utilities in California. It provides a summary of participation, DR strategies and incentives. Commercial buildings can reduce peak demand from 5 to 15percent with an average of 13percent. Industrial facilities shed much higher loads. For buildings with multi-year savings we evaluate their load variability and shed variability. We provide a summary of control strategies deployed, along with costs to install automation. We report on how the electric DR control strategies perform over many years of events. We benchmark the peak demand of this sample of buildings against their past baselines to understand the differences in building performance over the years. This is done with peak demand intensities and load factors. The paper also describes the importance of these data in helping to understand possible techniques to reach net zero energy using peak day dynamic control capabilities in commercial buildings. We present an example in which the electric load shape changed as a result of a lighting retrofit.

This project provides algorithms to perform demandresponse using the thermal mass of a building. Using the thermal mass of the building is an attractive method for performing demandresponse because there is no need for capital expenditure. The algorithms rely on the thermal capacitance inherent in the building?s construction materials. A near-optimal ?day ahead? predictive approach is developed that is meant to keep the building?s electrical demand constant during the high cost periods. This type of approach is appropriate for both time-of-use and critical peak pricing utility rate structures. The approach uses the past days data in order to determine the best temperature setpoints for the building during the high price periods on the next day. A second ?model predictive approach? (MPC) uses a thermal model of the building to determine the best temperature for the next sample period. The approach uses constant feedback from the building and is capable of appropriately handling real time pricing. Both approaches are capable of using weather forecasts to improve performance.

This report documents a field study of 78 small commercial customers in the Sacramento Municipal Utility District service territory who volunteered for an integrated energy-efficiency/demand-response (EE-DR) program in the summer of 2008. The original objective for the pilot was to provide a better understanding of demandresponse issues in the small commercial sector. Early findings justified a focus on offering small businesses (1) help with the energy efficiency of their buildings in exchange for occasional load shed, and (2) a portfolio of options to meet the needs of a diverse customer sector. To meet these expressed needs, the research pilot provided on-site energy efficiency advice and offered participants several program options, including the choice of either a dynamic rate or monthly payment for air-conditioning setpoint control. An analysis of hourly load data indicates that the offices and retail stores in our sample provided significant demandresponse, while the restaurants did not. Thermostat data provides further evidence that restaurants attempted to precool and reduce AC service during event hours, but were unable to because their air-conditioning units were undersized. On a 100 F reference day, load impacts of all participants during events averaged 14%, while load impacts of office and retail buildings (excluding restaurants) reached 20%. Overall, pilot participants including restaurants had 2007-2008 summer energy savings of 20% and bill savings of 30%. About 80% of participants said that the program met or surpassed their expectations, and three-quarters said they would probably or definitely participate again without the $120 participation incentive. These results provide evidence that energy efficiency programs, dynamic rates and load control programs can be used concurrently and effectively in the small business sector, and that communicating thermostats are a reliable tool for providing air-conditioning load shed and enhancing the ability of customers on dynamic rates to respond to intermittent price events.

Abstract Many utilities are obligated by state regulatory or legislative requirements to consider demandresponse (DR) as part of their resource planning process. There are several ways to incorporate DR into resource planning modeling and each has its advantages and disadvantages. We explore the current analytical frameworks for incorporating DR into long-term resource planning. We also consider whether current approaches accurately and realistically model DR resources in capacity expansion and production cost models and whether barriers exist to incorporating DR into resource planning models in a more robust fashion. We identify 10 specific recommendations for enhancing and expanding the current approaches.

Abstract Demandresponse (DR), which controls electric usage of customers when electric system reliability is jeopardised, attracts much societal attention. To realise a pragmatic DR, aggregators have to make well-customised requests for power saving to keep each customer comfortable in energy use. An engineering method is proposed here to design a DR aggregation service from the viewpoint of various customers’ comfort. The idea is to use an optimum resource allocation method that can provide quantitative information on how much electric power should be saved by each customer. The application validated the effectiveness of the proposed method.

The DemandResponse Spinning Reserve project is a pioneering demonstration showing that existing utility load-management assets can provide an important electricity system reliability resource known as spinning reserve. Using aggregated demand-side resources to provide spinning reserve as demonstrated in this project will give grid operators at the California Independent System Operator (CA ISO) and Southern California Edison (SCE) a powerful new tool to improve reliability, prevent rolling blackouts, and lower grid operating costs.In the first phase of this demonstration project, we target marketed SCE?s air-conditioning (AC) load-cycling program, called the Summer Discount Plan (SDP), to customers on a single SCE distribution feederand developed an external website with real-time telemetry for the aggregated loads on this feeder and conducted a large number of short-duration curtailments of participating customers? air-conditioning units to simulate provision of spinning reserve. In this second phase of the demonstration project, we explored four major elements that would be critical for this demonstration to make the transition to a commercial activity:1. We conducted load curtailments within four geographically distinct feeders to determine the transferability of target marketing approaches and better understand the performance of SCE?s load management dispatch system as well as variations in the AC use of SCE?s participating customers;2. We deployed specialized, near-real-time AC monitoring devices to improve our understanding of the aggregated load curtailments we observe on the feeders;3. We integrated information provided by the AC monitoring devices with information from SCE?s load management dispatch system to measure the time required for each step in the curtailment process; and4. We established connectivity with the CA ISO to explore the steps involved in responding to CA ISO-initiated requests for dispatch of spinning reserve.The major findings from the second phase of this demonstration are:1. Demand-response resources can provide full response significantly faster than required by NERC and WECC reliability rules.2. The aggregate impact of demandresponse from many small, individual sources can be estimated with varying degrees of reliability through analysis of distribution feeder loads.3. Monitoring individual AC units helps to evaluate the efficacy of the SCE load management dispatch system and better understand AC energy use by participating customers.4. Monitoring individual AC units provides an independent data source to corroborate the estimates of the magnitude of aggregate load curtailments and gives insight into results from estimation methods that rely solely on distribution feeder data.

3E 3E Findings from Seven Years of Field Performance Data for Automated DemandResponse in Commercial Buildings S. Kiliccote, M.A. Piette, J. Mathieu, K. Parrish Environmental Energy Technologies Division May 2010 Presented at the 2010 ACEEE Summer Study on Energy Efficiency in Buildings, Pacific Grove, CA, August 15-20, 2010, and published in the Proceedings DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information,

53E 53E Chilled Water Storage System and DemandResponse at the University of California at Merced J. Granderson, J.H. Dudley, S. Kiliccote, M.A. Piette Environmental Energy Technologies Division September 2009 Presented at the 9 th International Conference for Enhanced Building Operations, Austin, TX, November 17-18, 2009, and published in the Proceedings DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information,

340E 340E Design and Operation of an Open, Interoperable Automated DemandResponse Infrastructure for Commercial Buildings M.A. Piette, G. Ghatikar, S. Kiliccote, D. Watson Lawrence Berkeley National Laboratory E. Koch, D. Hennage Akuacom June 2009 Journal of Computing Science and Information Engineering, Vol. 9, Issue 2 DISCLAIMER This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the University of California, nor any of their employees, makes any warranty, express or implied, or assumes any legal responsibility for the accuracy, completeness, or usefulness of any information,

Abstract This paper proposes an energy offering strategy for wind power producers. A new trading plan is presented through which a wind power producer can employ demandresponse (DR) to maximize its profit. To consider DR, a new DR scheme is developed here. The proposed plan includes two steps: The first step takes place on a day-ahead basis. The corresponding decisions involve an initial offering schedule and preliminary DR arrangements for the following day. The second step coincides with the day of the energy delivery. A consecutive approach is proposed in which the wind power producer determines its final energy offer during each trading interval. Simultaneously, the required DR agreements for that interval are also confirmed. This approach is repeated until all periods of the day are covered. The proposed plan is formulated as a stochastic programming approach, where its feasibility is evaluated on a case of the Australian National Electricity Market (NEM).

The goal of this study was to demonstrate a demandresponse system that can signal nearly every customer in all sectors through the integration of two widely available and non- proprietary communications technologies--Open Automated DemandResponse (OpenADR) over lnternet protocol and Utility Messaging Channel (UMC) over FM radio. The outcomes of this project were as follows: (1) a software bridge to allow translation of pricing signals from OpenADR to UMC; and (2) a portable demonstration unit with an lnternet-connected notebook computer, a portfolio of DR-enabling technologies, and a model home. The demonstration unit provides visitors the opportunity to send electricity-pricing information over the lnternet (through OpenADR and UMC) and then watch as the model appliances and lighting respond to the signals. The integration of OpenADR and UMC completed and demonstrated in this study enables utilities to send hourly or sub-hourly electricity pricing information simultaneously to the residential, commercial and industrial sectors.

Energy Information Systems (EIS) for buildings are becoming widespread in the U.S., with more companies offering EIS products every year. As a result, customers are often overwhelmed by the quickly expanding portfolio of EIS feature and application options, which have not been clearly identified for consumers. The object of this report is to provide a technical overview of currently available EIS products. In particular, this report focuses on web-based EIS products for large commercial buildings, which allow data access and control capabilities over the Internet. EIS products combine software, data acquisition hardware, and communication systems to collect, analyze and display building information to aid commercial building energy managers, facility managers, financial managers and electric utilities in reducing energy use and costs in buildings. Data types commonly processed by EIS include energy consumption data; building characteristics; building system data, such as heating, ventilation, and air-conditioning (HVAC) and lighting data; weather data; energy price signals; and energy demand-response event information. This project involved an extensive review of research and trade literature to understand the motivation for EIS technology development. This study also gathered information on currently commercialized EIS. This review is not an exhaustive analysis of all EIS products; rather, it is a technical framework and review of current products on the market. This report summarizes key features available in today's EIS, along with a categorization framework to understand the relationship between EIS, Energy Management and Control Systems (EMCSs), and similar technologies. Four EIS types are described: Basic Energy Information Systems (Basic-EIS); DemandResponse Systems (DRS); Enterprise Energy Management (EEM); and Web-based Energy Management and Control Systems (Web-EMCS). Within the context of these four categories, the following characteristics of EIS are discussed: Metering and Connectivity; Visualization and Analysis Features; DemandResponse Features; and Remote Control Features. This report also describes the following technologies and the potential benefits of incorporating them into future EIS products: Benchmarking; Load Shape Analysis; Fault Detection and Diagnostics; and Savings Analysis.

Sample records for demand response case from the National Library of Energy Beta (NLEBeta)

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Demandresponse (DR)control can effectively relieve balancing and frequency regulation burdens on conventional generators, facilitate integrating more renewable energy, and reduce generation and transmission investments needed to meet peak demands. Electric water heaters (EWHs) have a great potential in implementing DR control strategies because: (a) the EWH power consumption has a high correlation with daily load patterns; (b) they constitute a significant percentage of domestic electrical load; (c) the heating element is a resistor, without reactive power consumption; and (d) they can be used as energy storage devices when needed. Accurately modeling the dynamic behavior of EWHs is essential for designing DR controls. Various water heater models, simplified to different extents, were published in the literature; however, few of them were validated against field measurements, which may result in inaccuracy when implementing DR controls. In this paper, a partial differential equation physics-based model, developed to capture detailed temperature profiles at different tank locations, is validated against field test data for more than 10 days. The developed model shows very good performance in capturing water thermal dynamics for benchmark testing purposes

63E 63E Mass Market DemandResponse and Variable Generation Integration Issues: A Scoping Study Peter Cappers, Andrew Mills, Charles Goldman, Ryan Wiser, Joseph H. Eto Environmental Energy Technologies Division October 2011 The work described in this report was funded by the Permitting, Siting and Analysis Division of the U.S. Department of Energy's Office of Electricity Delivery and Energy Reliability under Lawrence Berkeley National Laboratory Contract No. DE-AC02- 05CH11231. ERNEST ORLANDO LAWRENCE BERKELEY NATIONAL LABORATORY Disclaimer This document was prepared as an account of work sponsored by the United States Government. While this document is believed to contain correct information, neither the United States Government nor any agency thereof, nor The Regents of the

We introduce and analyze Markov Decision Process (MDP) machines to model individual devices which are expected to participate in future demand-response markets on distribution grids. We differentiate devices into the following four types: (a) optional loads that can be shed, e.g. light dimming; (b) deferrable loads that can be delayed, e.g. dishwashers; (c) controllable loads with inertia, e.g. thermostatically-controlled loads, whose task is to maintain an auxiliary characteristic (temperature) within pre-defined margins; and (d) storage devices that can alternate between charging and generating. Our analysis of the devices seeks to find their optimal price-taking control strategy under a given stochastic model of the distribution market.

Abstract The emergence of viable smart home technologies together with ambitious government initiatives for smart meter rollouts will provide a rich platform on which to develop demand side management strategies that aim to modify consumer's use of energy. In this work we develop such a platform that aims to ‘SWITCH’ behaviour patterns and ‘SWITCH’ on/off energy consuming appliances when they are not needed or when they could be utilised to benefit from on-site power generation or off-peak electricity. This platform was installed in 3 occupied domestic properties that form part of the Creative Energy Homes project at the University of Nottingham, UK. A total of 6 case studies are presented that investigate the impact of shifting the time of use of washing machines and dishwashers with varying levels of user engagement. A range of issues and user perceptions of the technology are presented and discussed.

Abstract As a form of renewable and low-carbon energy resource, wind power is anticipated to play an essential role in the future energy structure. Whereas, its features of time mismatch with power demand and uncertainty pose barriers for the power system to utilize it effectively. Hence, a novel unit commitment model is proposed in this paper considering demandresponse and electric vehicles, which can promote the exploitation of wind power. On the one hand, demandresponse and electric vehicles have the feasibility to change the load demand curve to solve the mismatch problem. On the other hand, they can serve as reserve for wind power. To deal with the unit commitment problem, authors use a fuzzy chance-constrained program that takes into account the wind power forecasting errors. The numerical study shows that the model can promote the utilization of wind power evidently, making the power system operation more eco-friendly and economical.

Abstract The high penetration of both Distributed Energy Resources (DER) and DemandResponse (DR) in modern power systems requires a sequence of advanced strategies and technologies for maintaining system reliability and flexibility. Real-time electricity markets (RTM) are the non-discriminatory transaction platforms for providing necessary balancing services, where the market clearing (nodal or zonal prices depending on markets) is very close to real time operations of power systems. One of the primary functions of \\{RTMs\\} in modern power systems is establishing an efficient and effective mechanism for small DER and DR to participate in balancing market transactions, while handling their meteorological or intermittent characteristics, facilitating asset utilization, and stimulating their active responses. Consequently, \\{RTMs\\} are dedicated to maintaining the flexibility and reliability of power systems. This paper reviews advanced typical \\{RTMs\\} respectively in the North America, Australia and Europe, focusing on their market architectures and incentive policies for integrating DER and DR in electricity markets. In this paper, \\{RTMs\\} are classified into three groups: Group I applies nodal prices implemented by optimal power flow, which clears energy prices every 5 min. Group II applies zonal prices, with the time resolution of 5-min. Group III is a general balancing market, which clears zonal prices intro-hourly. The various successful advanced RTM experiences have been summarized and discussed, which provides a technical overview of the present \\{RTMs\\} integrating DER and DR.

Abstract This paper uses a one-dimensional, physics-based model of a valve-regulated lead-acid (VRLA) battery to examine the impact of demandresponse on uninterruptible power supply (UPS) availability in a datacenter. Datacenters are facilities that provide services such as cloud computing, web search, etc. They are also large electricity consumers. An energy-efficient 15 MW datacenter, for instance, may pay $1 m per month for electricity. Datacenters often utilize VRLA batteries to ensure high reliability in serving their computational demand. This motivates the paper's central question: to what extent does the use of datacenter UPS batteries for demandresponse affect their availability for their primary purpose (namely, emergency power)? We address this question using a physics-based model of the coupled diffusion-reaction dynamics of VRLA batteries. We discretize this model using finite differences, and simulate it for different datacenter battery pack sizes. The results show that for a typical datacenter power demand profile, a VRLA battery pack sized for UPS functionality can provide demandresponse with only a minimal loss of UPS availability.

The output of renewable energy fluctuates significantly depending on weather conditions. We develop a unit commitment model to analyze requirements of the forecast output and its error for renewable energies. Our model obtains the time series for the operational state of thermal power plants that would maximize the profits of an electric power utility by taking into account both the forecast of output its error for renewable energies and the demandresponse of consumers. We consider a power system consisting of thermal power plants, photovoltaic systems (PV), and wind farms and analyze the effect of the forecast error on the operation cost and reserves. We confirm that the operation cost was increases with the forecast error. The effect of a sudden decrease in wind power is also analyzed. More thermal power plants need to be operated to generate power to absorb this sudden decrease in wind power. The increase in the number of operating thermal power plants within a short period does not affect the total opera...

With restructuring of the traditional, vertically integrated electricity industry come new opportunities for electricity demand to actively participate in electricity markets. Traditional definitions of power system ...

Abstract Projections of energy demand are an important part of analyses of policies to promote conservation, efficiency, technology implementation and renewable energy production. The development of energy demand is a key driver of the future energy system. This paper presents long-term projections of the Norwegian energy demand as a two-step methodology of first using activities and intensities to calculate a demand of energy services, and secondly use this as input to the energy system model TIMES-Norway to optimize the Norwegian energy system. Long-term energy demand projections are uncertain and the purpose of this paper is to illustrate the impact of different projections on the energy system. The results of the analyses show that decreased energy demand results in a higher renewable fraction compared to an increased demand, and the renewable energy production increases with increased energy demand. The most profitable solution to cover increased demand is to increase the use of bio energy and to implement energy efficiency measures. To increase the wind power production, an increased renewable target or higher electricity export prices have to be fulfilled, in combination with more electricity export.

The introduction of real time pricing in many wholesale market as well as the liberalisation process involving the retail market poses the attention over the measurement of demandresponse to time differentiated price signals. This paper shows an example of how to estimate elasticities of substitution across time using a sample of Italian industrial customers facing time-of-use (TOU) pricing schemes. The model involves the estimation of a nested constant elasticity of substitution (CES) input demand function, which allows estimating substitutability of electricity usage across hourly intervals within a month and across different months.

Abstract The dynamic economic emission dispatch (DEED) of electric power generation is a multi-objective mathematical optimization problem with two objective functions. The first objective is to minimize all the fuel costs of the generators in the power system, whilst the second objective seeks to minimize the emissions cost. Both objective functions are subject to constraints such as load demand constraint, ramp rate constraint, amongst other constraints. In this work, we integrate a game theory based demandresponse program into the DEED problem. The game theory based demandresponse program determines the optimal hourly incentive to be offered to customers who sign up for load curtailment. The game theory model has in built mechanisms to ensure that the incentive offered the customers is greater than the cost of interruption while simultaneously being beneficial to the utility. The combined DEED and game theoretic demandresponse model presented in this work, minimizes fuel and emissions costs and simultaneously determines the optimal incentive and load curtailment customers have to perform for maximal power system relief. The developed model is tested on two test systems with industrial customers and obtained results indicate the practical benefits of the proposed model.

Abstract In a smart(er) grid context, the existence of dynamic tariffs and bidirectional communications will simultaneously allow and require an active role from the end-user concerning electricity management. However, the residential end-user will not be always available to manage energy resources and decide, based on price signals and preferences/needs, the best response actions to implement or the best usage of the electricity produced locally. Therefore, energy management systems are required to monitor consumption/generation/storage and to make the best decisions according to input signals and the user's needs and preferences. The design of adequate algorithms to be implemented in those systems require the prior characterization of domestic electricity demand and categorization of loads, according to availability, typical usage patterns, working cycles and technical constraints. Automated demandresponse actions must be tailored and chosen according to this previous analysis of load characteristics. In this paper, a characterization of household electricity consumption is presented and an operational categorization of end-use loads is proposed. The existing potential for demandresponse to a diversified set of management actions is described and a tool to assess the impact of implementing several actions with different rates of penetration of energy management systems is presented. The results obtained show the potential savings for the end-user and expected changes in the load diagram with a decrease of the aggregated peak electricity demand and a smoothed valley.

Rapid growth in electricity network peak demand is increasing pressure for new investment which may be used for only a few hours a year. Residential air-conditioning is widely believed to be the prime cause of...